In recent years, in Vietnam, economy has been developing rapidly. To ensure rapid and sustainable economic growth, strong support from the energy sector is required. Governments in Vietnam have invested in numerous hydropower projects, many of which employ the EPC (Engineering, Procurement and Construction) contract. However, the EPC general contractors are facing many difficulties, resulting in schedule delays and considerable losses. This research is conducted to highlight the main risk factors in the delays of hydropower construction projects in Vietnam. The research employs the method of statistical calculations and risk analysis to obtain feedback from experts participating in similar projects. The research outcomes are as follows: identifying the risks that can cause delays in EPC hydroelectric construction projects in Vietnam; calculating and classifying the degree of impact of each risk to the progress of the construction. The practical significance of this study is to ensure the timely completion of projects, benefits for the investors, and the EPC general contractors.
Engineering Procurement and Construction (EPC) Risk Research EPC Hydropower Project Construction Projects1. Research Context and Proposed Research Orientation1.1. Research Context
The EPC contract of the hydropower projects in Vietnam is facing many difficulties due to slow progress in construction and delay in time of completion. There are numerous factors leading to slow construction progress. To identify these factors, the author analyzes the characteristics of hydropower projects combined with the opinions of experienced experts with hydropower projects in Vietnam. On this basis, hypotheses about risk models are developed.
In recent years in the Vietnam, more attention has been given to risk management of hydropower projects. For instance, Zhao Juelong (2008) [1] studied cases of EPC hydropower projects in Vietnam, proposed risk factors, and suggested ways to minimize risks and proposed management measures. Li Wei (2012) [2] , through the research of the Con River hydropower station in Vietnam, showed risks in project procurement, contract construction, material purchases, risks of delays in the project, and the increased expenses in construction, Jixin Wei and Liujian Zhe, through the “The whole process of overseas engineering project risk management” [3] studied about project risks. The most general characteristics of hydropower projects following the EPC in Vietnam as follows: 1) The use of EPC in Vietnam is relatively new, and project management is poor; 2) At the construction sites, the people’s culture standard is low, causing various difficulties; 3) Resettlement, land withdrawal and handover for the construction contractors are complex; 4) Hydropower equipment for the projects must be imported from abroad with complex procedures, difficult shipment, and slow assembly; 5) In Vietnam currently keep high inflation rates, which affect the purchase of required materials, machines, and equipment; 6) Natural conditions such as climate, hydrology, topography, and geological conditions lead to further complications; 7) The sub-contractors’ construction capacity is poor; the domestic construction technology has low productivity, and is not up to standard; 8) The infrastructure and traffic facilities for transport are poor; machine and equipment transportation encounter many difficulties, leading to delays, etc.
In the above mentioned literature, the author finds that research on risks in hydropower projects in Vietnam is still limited. With the reality of tardy construction projects and progress delays, the author deems it urgent to conduct research on risks involved in delaying the construction progress of the hydropower project using EPC in Vietnam .
The research employs the method of statistical calculations and risk analysis to obtain feedback from experts participating in similar projects. The research outcomes as follows: identifying the risks that can cause delays in EPC hydroelectric construction projects in Vietnam; calculating and classifying the degree of impact of each risk to the progress of the construction.
1.2. Proposal for Project Orientation1.2.1. Project Orientation
Using the public information on the Internet, television, newspapers and other documents, the author carried out on-site interviews with experts and officers participating in EPC projects. On the basis of these opinions, the author hypothesized the risk factors, and calculated statistical with SPSS and AMOS software to analyze and complete the objective: research on delay risks of EPC hydropower construction projects in Vietnam.
1.2.2. Research Structure
The structure of this research includes three main parts: 1) The risk hypothesis and the impacts of risks on construction schedule; 2) Calculation and inspection of risk; 3) Controlling and limiting risks.
2. Risk Variables and Risk Model Selection2.1. Risk Variables
Through the analysis of information and consultation of experts’ opinions, we summarize the characteristics of the hidden risks leading to delays in the construction progress of the hydropower projects. Based on these characteristics, the main reasons leading to the construction progress delays can be divided into the following groups: Risk from contracts (B1), Risk from politics and law (B2), Risk from technology (B3), Risk from natural conditions and social environment (B4), Risk from economy (B5), Risk from management (B6), Risks from EPC general contractors (B7). Table 1 is systematic table of risk factors.
2.2. Selection of Variables for Risk Calculation Models
Based on the above hypothesis of risks, the author summarized and proposed the hypothesis of the risk model affecting progress in Figure 1.
Specifies the assumptions of the risk system model affecting the progress
Hypothesis of risk group
Objective for evaluation
Risk group level 1 (Hidden risk cause variables)
Risks level 2 (Hypothesized risk variables)
Delaying the construction progress
Risk from contracts (B1)
Unfair contract terms (b1.1) Uncertain and unclear contract terms (b1.2) Fixing the EPC contract price (b1.3) Second language contracts with misleading clauses (b1.4)
Risk from politics and law (B2)
The relationship of investor, general contractor with the authority and relevant departments (b2.1) Regional political change (b2.2) Laws and regulations of the management agencies (b2.3)
Risk from technology (B3)
Technical design (b3.1) Negative survey data (b3.2) Construction drawings (b3.3) Inspection of technical and drawings design (3.4)
Risk from natural conditions and social environment (B4)
Geology, topography, and hydrography (b4.1) Ethnic groups and religions (b4.2) Transportation outside of the construction site (b4.3) Safety and security (b4.4)
Risk from economy (B5)
Finances of the investor (b5.1) Interest rate fluctuations (b5.2) Inflation (b5.3) Financial capacity of EPC general contractors (b5.4)
Risk from management (B6)
Poor progress management (b6.1) Construction projects monitoring team (b6.2) Poor quality work requiring repair (b6.3) Construction safety (b6.4) Inharmonious management among the EPC general contractors (b6.5)
Risk from EPC general contractors (B7)
Purchasing materials, supplies, equipment and machines (b7.1) Difficulties with subcontractors (b7.2) Equipment installation and commissioning (b7.3) Poor construction from the EPC general contractors (b7.4)
Consequences of the risk factors (B8)
Prolong the construction progress (b8.1) Increase in construction costs (b8.2)
3. Calculation and Verification of the Hypothesis Model3.1. Data and Supporting Software
From the hypothesis of risks in Table 2, the author did an investigation using slips with 5 levels of risk assessment as follows.
Investigation using slips with 5 levels of risk assessment
1) Risk factors and risk consequences
Impact level of construction progress delays
Low (1)
Rather low (2)
Medium (3)
High (4)
Very high (5)
Risk factors of risk group at level 2
2) Consequences of risk factors
<10%
10% - 20%
20% - 30%
30% - 40%
>40%
Prolong the construction progress. Increase in construction costs
3.2. Verification Results3.2.1. Calculate the Cronbach’s Alpha Reliability Coefficient
The Cronbach’s Alpha coefficient value (α) in the interval from 0 - 1, if α < 0.6 is insufficient reliability. In the survey data for research, we can use α > 0.6 achieved reliability, can use for analysis, (Hair J F, Anderson R E 1998) [4] ; (Slater 1995) [5] . Using SPSS software to conduct the calculations and testing, the author eliminated the variables with “Corrected Item-Total Correlation” <0.3) [4] - [12] (eliminated the variables: b1.1, b1.4, b2.2, b4.2, b5.2, b6.3, b6.4, b6.5, b7.4). The Cronbach’s Alpha was then calculated, results in Table 3.
The Cronbach’s Alpha coefficient α > 0.6, which holds enough reliability to permit the use of the survey results [4] [5] . After eliminating the unqualified variables, the results are as shown in Table 3.
3.2.2. Calculate and Analyze the Discovery Factors
Before performing the SEM model simulation, it is necessary to conduct the calculation and analysis of the discovery factors, investigate the main factors, including the observation variables (survey questions), and test the reliability as shown in Table 4. In the factor analysis of SPSS, the factor deduction method “Principal Axis Factoring” and the horizontal rotation method, Promax, were used.
The results are required to obtain a KMO ≥ 0.5 (Hair et al., 2006) [6] , testing coefficient with the statistical meaning Bartlett (Sig < 0.05) (Hair et al., 2006) [6] .
The results shown in Table 4, the KMO test coefficient features the value of 0.705 (>0.5), and the coefficient with the Bartlett statistical meaning of (Sig < 0.05). This proves the survey results have reliability; the question hypotheses are reasonable; the survey data is proper, and objective. The data is sufficient for conducting analysis in the following steps. Additionally, each variable features the factor loading coefficient larger than 0.5; Jabnoun & Al-Tamimi (2003) [7] providing that the factor loading coefficient of the variables is not less than 0.3, Gerbing & Anderson (1988) [8] clarifies the percentage of variance higher than 50%. Initially, the author used 18 variables, based on the standard of the factor loading coefficient larger than 0.5. The author gradually deleted the variables b3.2, then the factors analysis was conducted. Seven factors were chosen, B1, B2, B3, B4, B5, B6, B7, whose percentage of variance reached 56.5%, higher than the standard value of 50%, as shown in Table 5.
3.2.3. Calculate and Analyze the Factors
Analyze and verify the combination of factors
The author used the AMOS20.0 software for 8 assumption factors and 19 assumption risk variables to calculate the standardized factor loading coefficient of the 19 assumption risk variables in the interval of 0.501 to 1.038 (Table 6). In accordance with the standard factor loading coefficient >0.5, which shows the assumption risk variables for the groups of combined factors in a close relationship; the hypothesized risk variables have the largest effect on the factors group, as pointed out in the model.
Calculate verify the efficiency of the factors
The reliability value of the CR combination of the minimum factor is 0.75. All values are larger than the standard coefficient of 0.5 [4] , proving that the assumption variables compared with the assumption variables models is highly consistent. The author calculated the Average Variance Extracted, AVE, found the abnormal average values, and conducted the confirmation of convergence of assumption variables in the model. The result showed the AVE value is 0.51 to 0.74, All values are larger than the standard coefficient of 0.5 [9] , proving the assumption variables compared with the factors with good convergence.
Verify the proposed model
Shown in Figure 2 and from the following Table 7, it is possible to conclude that the assessment result is
The structure of SEM model and assessment result
Cronbach’s Alpha
Group of hidden cause variables
B1 (b1.2; b1.3)
B2 (b2.1; b2.3)
B3 (b3.1; b3.2; b3.3; b3.4)
B4 (b4.1; b4.3)
B5 (b5.1; b5.3; b5.4)
B6 (b6.1; b6.2)
B7 (b7.1; b7.2; b7.3)
B8 (b8.1; b8.2)
Sum of the variables
Cronbach’s Alpha
0.799
0.719
0.726
0.812
0.663
0.805
0.684
0.69
0.78
KMO and Bartlett’s Test, total variance explained
KMO and Bartlett’s Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.
0.705
Sig.
0.000
extremely ideal; and further indicates the proposed model for the survey data is of reasonable design.
Review the parameters of the model
According to the parameters of the regression model given in Table 8, the values (p) of the assumption items are also less than 0.05, which explains the reliability level of over 95%. The risk factors strongly affected the extension of the construction progress.
Pattern Matrixa
Factor
1
2
3
4
5
6
7
b1.2
0.713
b1.3
0.922
b2.1
0.911
b2.3
0.651
b3.1
0.855
b3.3
0.528
b3.4
0.611
b4.1
0.813
b4.3
0.861
b5.1
0.547
b5.3
0.655
b5.4
0.681
b6.1
0.775
b6.2
0.893
b7.1
0.511
b7.2
0.743
b7.3
0.691
Average variance extracted and AVE values
The hypothesized variables
Factor loading coefficients
Errors of variables
CR
AVE
Risk from contracts (B1) Uncertain and unclear contract terms (b1.2) Transportation outside the construction site (b1.3)
0.905 0.727
0.139 0.324
0.85
0.74
Risk from politics and law (B2) The relationship of investor and general contractor with the authority and relevant departments (b2.1) Laws and regulations of management agencies (b2.3)
0.933 0.683
0.141 0.384
0.83
0.72
Risk from techniques (B3) Technical design (b3.1) Construction drawings (b3.3) Inspection of technical and drawings design (b3.4)
0.727 0.705 0.682
0.467 0.493 0.502
0.75
0.51
Risk from natural conditions and social environment (B4) Geology, topography, and hydrography (b4.1) topography (b4.3)
0.952 0.731
0.110 0.591
0.80
0.67
Risk from economy (B5) Finances of the investor (b5.1) Inflation (b5.3) Financial capacity of the contractors (b5.4)
0.827 0.501 0.596
0.215 0.458 0.457
0.77
0.53
Risk from management (B6) Poor management of progress (b6.1) Construction items monitoring unit (b6.2)
0.850 0.816
0.264 0.283
0.84
0.72
Risk from the EPC general contractors (B7) Purchasing materials, equipment, and machines (b7.1) Sub-contractor (b7.2) Equipment installation and commissioning (b7.3)
0.756 0.693 0.636
0.287 0.416 0.423
0.79
0.56
Consequences of the risk factors (B8) Prolong the construction progress (b8.1) Increase construction costs (b8.2)
1.038 0.501
0.063 0.576
0.79
0.68
Absolute appropriate index and information index
Absolute appropriate index
Chi-square/df
GFI
TLI
CFI
RMSEA
Value
1.284
0.937
0.901
0.927
0.033
Assessment criteria
Hair et al., 1998 [4] think that 1 < Chi-square/df < 3 is very good
Segar, Grover, 1993 [10] and Chin, Todd, think that >0.9 is very good.
Taylor, Sharland, Cronin, Bullard, 1993 [11] think that RMSEA <0.05 is very good
The values: C.R., P, Standardized coefficients
Assumption
Non-standardized coefficients
S.E.
C.R.
P
Standardized coefficients
Consequences of risks (Prolong the construction progress) ← Risk from contracts (B1)
0.211
0.087
2.416
0.016
0.136
Consequences of risks (Prolong the construction progress) ← Risk from the politics and law (B2)
0.236
0.093
2.528
0.011
0.146
Consequences of risks (Prolong the construction progress) ← Risk from techniques (B3)
0.236
0.105
2.245
0.025
0.167
Consequences of risks (Prolong the construction progress) ← Risk from natural conditions and social environment (B4)
0.162
0.064
2.532
0.011
0.143
Consequences of risks (Prolong the construction progress) ← Risk from economy (B5)
0.440
0.126
3.506
***
0.237
Consequences of risks (Prolong the construction progress) ← Risk from management (B6)
0.173
0.085
2.037
0.042
0.139
Consequences of risks (Prolong the construction pro.) ← Risk from the EPC general contractors (B7)
0.331
0.111
2.985
0.003
0.220
Note: ***Indicate the value less than 0.001.
4. Conclusions
The work achieved includes the following:
1) Recognizing the risks existing in the EPC hydropower projects in Vietnam, thereby establishing the risk factor model for projects in Vietnam.
2) Based on those risk models, calculating, analyzing and carefully evaluating the risks to determine the 17 the main reason causes leading to the delays of construction progress of the projects.
3) Discovering the levels of risk impacts to construction progress finds that the largest risk factor is Risk from the economy (B5), which can severely delay the construction progress. The remaining factors from high to low impact level are: Risk from the EPC general contractors (B7); Risk from techniques (B3); Risk from the politics and law (B2); Risk from natural conditions and social environment (B4); Risk from the management (B6); Risk from contracts (B1).
These efforts have achieved the goals set by the original thesis: research on the risk of delay in construction of hydropower projects, Procurement and Construction (EPC) in the Vietnam.
Research results show overall objective situation EPC hydropower projects in Vietnam . Based on the results of this thesis, recommendations have been proposed regarding the full understanding of the risk factors of EPC project constructions to enhance risk management, as follows: Firstly, it is necessary to reinforce the theory of risk management, and continuously summarize and accumulate the experiences in the actual construction process to manage the risks of all similar projects. Secondly, before the construction, it is essential to consider the characteristics and circumstances of each given project, and continue to determine and assess each stage of hidden risk factors that may occur in order to control and restrain them.
Cite this paper
Mai Sy Hung,Jianqiong Wang, (2016) Research on Delay Risks of EPC Hydropower Construction Projects in Vietnam. Journal of Power and Energy Engineering,04,9-16. doi: 10.4236/jpee.2016.44002
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