ANALYSIS OF THE IMPACT OF COSTS ON THE TOTAL INVESTMENT AT CHỢ CỒN COMBINED APARTMENT AND SHOPPING MALL PROJECT
Ho Van Minh1,a,
Pham Phuong Nam1,b,
Nguyen Son Lam1,c
1Faculty of Construction, Ho Chi Minh City University of Technology (HUTECH)
Email: (a) phanminh017@gmail.com; (b)pp.namqlxd@gmail.com; (c) ns.lam@hutech.edu.vn
Abstract: The study analyzes the impact of costs on the total investment of Chợ Cồn combined apartment, and shopping mall project in Da Nang City, and figures out the correlation between costs, and total investment. This study also evaluates costs' impact on investment decisions, and proposes solutions to minimize risks, and optimize total investment. The research methods include risk assessment, sensitivity analysis, and correlation assessment between costs, and total investment. The results help project managers better understand the correlation between costs, and total investment, make effective decisions, and propose solutions to reduce risks, and optimize the project. The article also proposes specific solutions to ensure success, and sustainability for Chợ Cồn combined apartment, and shopping mall project. The results, and comments can be applied to similar construction projects, contributing to the development of the field of project management, and investment.
Keywords: Crystal Ball, Correlation assessment, Risk analysis, Monte Carlo, Total investment
1. Raising the issue
In construction project research, many international, and domestic studies have focused on the impact of cost overruns on total investment. The paper "The Impact of Cost Overruns on Construction Projects: A Review of the Literature" by Khan, and colleagues [1] is a comprehensive work synthesizing studies on the impact of cost overruns in global construction projects. However, this paper only focused on analyzing published studies without going into detail about influencing factors, and not mentioning measures to mitigate cost overruns. The study "The impact of cost overruns on construction projects in the United States" by Ford, and colleagues [2] focused on surveying the impact of cost overruns in construction projects in the United States. This paper reported research results on the level of cost overruns, and factors influencing cost overruns but did not mention measures to mitigate cost overruns. The study "The impact of cost overruns on construction projects in the United Kingdom" by Hillson, and colleagues [3] focused on studying the impact of cost overruns on construction projects in the United Kingdom. This paper provided research results on the level of cost overruns, and factors influencing cost overruns but did not discuss measures to mitigate cost overruns. Some domestic papers have also been conducted to understand better the correlation between cost factors, and total construction investment. Among these studies, three papers are notable. The paper "Đánh giá tác động của các yếu tố chi phí lên tổng mức đầu tư xây dựng công trình xanh" by Nguyễn Thị Thu Hương, and colleagues [4] examined all cost factors affecting total investment in green building construction. This paper used a scientific methodological approach combining theoretical, and empirical analysis to evaluate the impact of cost factors. The paper provides useful information for investors, project owners,, and construction project managers of green buildings. However, the scope of research was limited to green buildings in Vietnam, and was not compared with similar studies worldwide. The paper "Phân tích tác động của chi phí vật liệu lên tổng mức đầu tư xây dựng" by Nguyễn Thị Thu Thảo, and colleagues [5] focused on the impact of material costs on total construction investment. This paper used regression analysis methods, and actual data from construction projects in Vietnam. The research results showed that material costs have the greatest impact on total construction investment. However, the paper only considered the impact of material costs on total construction investment, and did not consider the impact of material costs on other factors of construction projects. The paper also did not propose solutions to mitigate the impact of material costs on total construction investment. The paper "Đánh giá tác động của chi phí nhân công lên tổng mức đầu tư xây dựng" by Nguyễn Thị Thu Hương, and colleagues [6] focused on the impact of labor costs on total construction investment. From these studies, it can be seen that the impact of cost overruns on total investment in construction projects is an important issue, and significantly affects the effectiveness, and success of projects. However, current research has not focused on a detailed analysis of influencing factors, and measures to mitigate cost overruns. Therefore, to achieve the research objective of the paper "Analyzing the impact between costs on a total investment of Chợ Cồn combined apartment, and shopping mall project ", it is necessary to research factors, and measures related to cost overruns in construction projects.
2. Determining the functions, and total investment construction cost of the project
Based on the locality's sustainable development requirements, and the area's actual needs, Chợ Cồn combined apartment, and shopping mall project was formed to meet the demand for quality living space, and comprehensive, convenient services for residents. This article aims to determine the detailed functions, and scales of the project's construction items, and the total estimated investment. This is an important basis for analyzing the impact of costs on the investment efficiency of the project, and proposing solutions to reduce risk to increase implementation effectiveness. The project is at 90 Hung Vuong Street, Hai Chau 1 Ward, Hai Chau District, Da Nang. Residential construction standards are determined according to Vietnamese standard No. 04:2021/BXD set by the Ministry of Construction. [7]. The project is divided into two main areas: the residential area, and the commercial, and service area. The residential area is designed as 12-22 stories high apartment blocks. The commercial, and service areas will be developed with supermarkets, shopping centers, dining areas, gardens,, and parking lots. Combining multiple functions aims to provide convenient, harmonious living environments for residents. The article will be divided into two parts. The first part will list the functions of each area of the project. The second part will estimate the total investment based on the project's technical specifications. The results will be used to analyze the impact of costs on the investment efficiency of the project.
Figure 1 - Overview of residential complex combined with Chợ Cồn commercial center.
2.1. Summary of project service functions.
Based on the thorough research of the detailed master layout drawings, this paper will conduct a comprehensive, and accurate analysis, and quantification of the planned functions to serve the project's overall goals. Specifically, the residential area is divided into three different types of apartments based on the bedroom criteria: one-bedroom, two-bedroom, and three-bedroom apartments. For each apartment type, the paper statistically enumerates the number of apartments, and determined the average suitable area. In addition, the commercial, and service area is divided into four main functional areas: supermarket area, food court, shopping area, and entertainment area. For each functional area, the paper also clearly provides the specific construction area allocated to each area (Table 2). Based on the above meticulous analysis, and quantification, this paper will summarize the total construction area of the entire project in detail.
Area
Total area (square meters)
Apartment type (square meters)
Public block (square meters)
Ancillary area
Three-bedroom unit one
Three-bedroom unit two
Two-bedroom unit one
Two-bedroom unit two
Two-bedroom unit three
Commercial, and service area
Nursery room
Community activity area
Car park area
Basement
21.780
18.200
3.580
Basement floor one
10.890
9.100
1.790
Basement floor two
Building tower block
91.648
7.552
6.048
4.128
12.240
2.752
30.503
300
233
-
27.620
Building base block
38.829
7.793
First-floor floor
10.100
9.247
220
Second-floor floor
6.066
5.125
940
Third floor
7.260
5.917
1.343
Fourth floor
6.762
5.953
809
Fifth floor
6.767
4.259
2.507
Sixth floor
1.874
52.819
19.827
Seventh floor
3.121
472
378
258
765
172
1.076
Eighth floor
Ninth floor
Tenth floor
Eleventh floor
Twelfth floor
Thirteenth floor
Fourteenth floor
Fifteenth floor
Sixteenth floor
Seventeenth floor
Eighteenth floor
Nineteenth floor
Twentieth floor
Twenty-first floor
Twenty-second floor
Rooftop floor
2.883
Included in the service, and public trade coefficient
Included in the housing coefficient
32.720
Construction floors do not include basements
Construction floors include basements
113.428
2.2. Determining the total investment of the project
After analyzing, and determining the functional use of each area within Chợ Cồn combined apartment, and shopping mall project, along with the total construction area explained earlier, this section will present the process of determining the total investment based on the quantified technical specifications. Specifically, the project's total investment is divided into 7 main cost groups based on Circular No.11/2021/TT-BXD[8], including land cost, construction cost, equipment cost, project management cost, investment, and construction consulting cost, other costs, and contingency costs. Based on detailed design drawings, and cost estimates, the article estimated the specific figures for each cost group mentioned above, and summarized them in (Table 2).
No
Cost Item
Before-tax (billion VND)
Tax
(billion VND)
After-tax (billion VND)
Symbol
One
Land cost
1225,00
98,00
1323,00
GBT, TDC
Two
Construction cost[9]
1066,04
85,28
1151,32
GXD
Three
Equipment cost[9]
168,19
13,45
181,64
GTB
Four
Project management cost[10]
13,06
0,14
13,20
GQLDA
Five
Investment, and construction consulting cost
[10], [11]
24,13
1,93
26,06
GTV
Six
Other costs[12], [13], [14]
34,53
2,76
49,73
GK
Seven
Contingency cost[8]
130,60
143,66
GDP
Total
2.661,55
241,63
2.888,62
VTM
Continuing the presentation of the total construction investment of the Chợ Cồn mixed-use residential, and commercial center project in (Table 1), the article further supplements more detailed information about the investment cost structure by building two charts (Figure 2) (Figure 3).
Figure 2 - Chart analyzing investment costs (%)
Figure 3 - Chart showing investment cost breakdown (billion VND)
The two charts (Figure 2) illustrate the percentage breakdown of the total investment allocation according to each cost group of the project, showing that land costs account for the largest proportion at 45.8%, of which construction costs account for approximately 39.86% of total cost, corresponding to Figure 3 which describes land costs more clearly at 1,323 billion VND, and construction costs of 1,151 billion VND. Using illustrative charts has helped readers easily grasp the project's cost structure visually, enabling them to assess the key cost factors that need attention to minimize project risks.
After determining, and summarizing the functional use, and construction area of the main components in the Chợ Cồn mixed-use residential, and commercial center project, the next step of the study is to determine the estimated total investment of the entire project. This provides a quantitative basis for evaluating the impact of cost factors on the total investment. Specifically, the total project investment is calculated based on the typical civil construction price list in Da Nang in 2024, and adjusted according to the region, and type of construction coefficients. For each major construction component, such as structure, infrastructure, fire prevention, and firefighting equipment, costs are calculated based on Table 2, and technical staff serve as the basis for cost analysis in subsequent sections. After noting the main contents in determining the project's total investment, the article will delve deeper into analyzing risks that may affect the total investment using the Monte Carlo simulation risk modeling software Crystal Ball[15]. Specifically, in this section, important variables affecting the total investment, such as material, labor, and construction costs, will have probability distributions constructed, and their impacts assessed through Monte Carlo simulation. This helps evaluate investment risks more comprehensively, proposing appropriate control measures to ensure the overall effectiveness of the project.
3. Risk analysis using Crystal Ball software
In this analysis, the author describes the process of analyzing project risks using Monte Carlo simulation tools in Crystal Ball [15] software. First, a mathematical model is built to reflect the relationship between main cost factors, and total investment by identifying variables, and probability distributions based on actual collected data. Next, the article will apply the Monte Carlo simulation algorithm in Crystal Ball to reproduce the probability distribution of the total investment based on the probabilistic fluctuations of risk factors. The simulation results will be evaluated to examine the volatility of the total investment, and the probability of exceeding the estimated cost in order to adjust more appropriate risk management measures for the project. Below are the parameters used as inputs for the Monte Carlo simulation (Table 3).
Table 3. Cost Parameters for Monte Carlo Simulation
Content
Minimum
Maximum
Likeliest
2%
6%
1.323
1.297
1.402
Construction cost
1.151
1.128
1.220
Equipment cost
182
178
193
Project management cost
13
14
26
28
Other costs
50
49
53
Contingency cost
144
141
152
Total investment
2.889
3.1. Risk assessment
Variations in costs are an important factor affecting the initial estimated total costs in construction projects. In this study, the author analyzes project risks based on variations between costs, and their impact on total costs, and project stability, by applying Crystal Ball [15] software. The author uses historical data on cost variations ranging from 2% to 6% deviation, and applies the Monte Carlo simulation method to assess risks, and propose optimal solutions for the project.
Figure 4 - Risk chart of Chợ Cồn Mixed-use Residential, and Commercial Center Project
Based on the results of 100,000 Monte Carlo simulations with a 2-6% fluctuation range for cost factors in the investment effectiveness assessment model of the project, the paper collected, and summarized important statistical figures. Accordingly, the base case value of the model was determined to be 2,889 billion VND. The analysis showed that the average value of 100,000 simulations reached 2,927 billion VND, higher than the base value. The standard deviation was only 30 billion VND, reflecting that the level of fluctuation in the simulation results was within the 2-6% limit compared to the base value. The highest, and lowest values also fell within the forecast range. The above results indicate that the project is feasible, and effective when the risk from cost fluctuations is low.
3.2. Sensitivity analysis
Here, the author aims to analyze the sensitivity of each input cost factor to the total result, which is the project's total investment, through the Monte Carlo simulation method. Specifically, the paper will evaluate the impact of a single percentage (%) fluctuation on the three cost factors on the total investment value. By comparing the average value when costs change, the study can determine which factor has the strongest or weakest impact. The analysis results will be presented in tables, and charts, from which the risks of each cost group can be more accurately assessed when the project is implemented.
Figure 4 - Sensitivity chart of Chợ Cồn Mixed-use Residential, and Commercial Center Project
Figure 4 - Sensitivity data of the Chợ Cồn Mixed-use Residential, and Commercial Center Project
Based on the results of implementing the Monte Carlo simulation, and summarizing the overall results, the report further evaluates the sensitivity of each type of input cost to the final result, which is the project's total investment, through the data analysis provided. Specifically, the "ContributionToVariance" column shows the percentage contribution of each cost item to the variation (variance) of the total capital. The results show that land costs, and construction costs accounted for 56.9%, and 42.1% of fluctuations respectively, which are the two most influential factors. The "RankCorrelation" column analyzes the correlation relationship between cost fluctuations, and total capital fluctuations through the correlation coefficient. Therefore, land, and construction costs have a very strong positive linear correlation with total capital of 0.74, and 0.63, respectively. Thus, the above sensitivity analysis confirms that land, and construction costs play the most important role in influencing fluctuations in the project's total investment.
3.3. Correlation analysis
Following the previous sensitivity analysis of each input cost, section 3.3 evaluates the interactive relationships between these costs through statistical data processing methods. Specifically, the study will apply the Pearson correlation coefficient (r) to quantify the level of linear correlation between pairs of costs. The results will identify cost pairs with positive or inverse correlations, and evaluate correlation strength. Principal component analysis is also applied to explain the variation of total investment through the contribution of each cost factor. Assessing the relationships between costs will provide a scientific basis for evaluating the stability of the project when input factors fluctuate in different directions.
Figure 5 - Correlation chart of the Chợ Cồn Mixed-use Residential, and Commercial Center Project
From the correlation chart, and analysis of the information presented in the figure, a clear correlation between cost items, and the project's total investment can be seen. In particular, land, and construction costs are determined to be the factors with the direct, and most important impact on total investment, accounting for 60-75% of total capital. This indicates that controlling land costs, and construction costs is very important, as fluctuations in them will directly impact the project's total budget. Secondly, equipment costs account for 15-25% of the total, in second place contributing to total investment. Fluctuations in these costs will also affect the total expenditure budget. Other costs still influence the total costs of the project. This shows that these costs have a linear correlation, and are dependent on each other. Strict control of the two largest cost items will make an important contribution to determining an effective investment option, and ensuring maintenance of the original capital level for the project.
4. Conclusions, and Recommendations
4.1. Conclusions
Through the process of researching, and applying statistical analysis methods, Monte Carlo simulation on Crystal Ball [15] software to evaluate the impact of cost factors on the total investment of the project, the study has come to the following main conclusions: Land cost, and construction cost are the two main cost factors that have the strongest influence on the total investment of the project, accounting for a large proportion, and having the highest level of fluctuation. These two costs have a very strong linear correlation with the total investment, with correlation coefficients of 0.74, and 0.63, respectively. The results of the Monte Carlo simulation show that the risk due to fluctuations in cost factors is within the allowable threshold, affirming the project's feasibility. In addition to the above conclusions, the study also drew the following additional points: Land, and construction costs have a strong impact on the total investment, and intersect very closely with each other. When one-factor changes, it will lead to a change in the other factor. This requires strict control of both factors during project implementation. The Monte Carlo simulation method gives relatively stable results but only reflects a preliminary risk assessment. It is necessary to thoroughly study the cost factors, and project implementation stages to provide a more accurate risk assessment. The statistical analysis methods, and simulation methods applied in the study were preliminary, and need further development of research methods to evaluate the impact of costs on project investment effectiveness more comprehensively.
4.2. Recommendations
Based on the results of the analysis, and evaluations in this study, the author would like to put forward the following recommendations: It is necessary to develop strict control plans for land costs, and construction costs, the two main cost factors affecting the total investment. Applying measures such as contract adjustments, and strict monitoring of payment schedules... helps limit fluctuations in these two factors. Continue researching the interaction of land, and construction costs, analyzing the impact of fluctuations in one factor on the other to have appropriate response scenarios. Supplementing the content of assessing risks arising during project implementation will give a better basis for improving the risk management plan, and applying more advanced analytical methods to produce more accurate, and effective results in assessing the impact of costs on the degree of project success.
Based on the initial research results on evaluating the impact of costs on the total project investment, I propose some directions for further research to expand, and deepen the issue: Conducting investigations, and field surveys of project owners, and construction contractors to collect more detailed data on fluctuations in factors affecting costs. Developing mathematical models that more clearly describe the intrinsic relationships between cost factors, and the project implementation process. Studying the evaluation of risk management effectiveness by comparing different cost control measures at actual projects. Applying advanced simulation methods such as dynamic system simulation to study the long-term impacts of risks. Expanding the scope of research to other construction investment sectors such as transportation, energy…
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