Cost Performance Comparison of Road Construction Projects Considering Bidding Condition and Project Characteristics

Developing road infrastructure facilities is important because it directly affects national competitiveness and has significant socio-economic ripple effects throughout the country. However, road construction projects are vulnerable to various risks and prone to cost overruns because they are funded by large-scale national budgets and conducted over long time periods. Therefore, tracking the changes in construction costs from planning to completion and providing insights for similar future projects is essential for successful project planning and management. Considering the bidding conditions and project characteristics of road construction projects, this study comparatively analyzed the construction cost growth of 170 road construction projects based on the bid award rate and facility-specific project characteristics, such as construction type, contract method, facility capacity, and construction cost components. This study analyzed the differences in cost performance between various sample groups using non-parametric tests (Mann–Whitney U test and Kruskal–Wallis test), considering the non-normality of the collected sample. In addition, this study conducted multiple regression analysis to examine the causal relationship between all variables used in the analysis and cost performance and to identify critical factors. The results indicated that the construction cost growth of the group with a bid award rate of less than 70% was higher compared to that of other groups. Furthermore, the differences in construction cost growth based on project characteristics were more pronounced in the following groups: construction types (expansion/renovation and complex), contract method (long-term continuous), road length (≥7.5 km), % of bridge/tunnel length (<10%), construction cost (≤USD 100 mil.), % of direct construction cost (≥70%), and % of bridge/tunnel cost (both less and more than 50%). Furthermore, the regression model showed that % of direct construction cost, bid award rate, total road length, and contract method were shown to be critical factors in construction cost growth, which implies the importance of indirect cost management, PDS selection decisions that affect bid award rates, and risk management for complex projects from the perspective of construction cost growth management. These results empirically demonstrate that bidding conditions and project characteristics are key to understanding the pattern of construction cost growth in road construction projects. Hence, this study provides significant references that can be used by policy makers and clients to estimate cost buffers for future road projects.

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Publication Details

Journal
Sustainability
Published
2024-11-19
DOI
https://doi.org/10.3390/su162210083
Citations
2
Primary Topic
BIM and Construction Integration
Type
article
Field-Weighted Citation Impact
0.53

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article

Cost Performance Comparison of Road Construction Projects Considering Bidding Condition and Project Characteristics

Kangwook Lee
2 citations
Sustainability
BIM and Construction Integration
0.53
article

Cost Performance Comparison of Road Construction Projects Considering Bidding Condition and Project Characteristics

Kangwook Lee
article en
2 citations

Abstract

Developing road infrastructure facilities is important because it directly affects national competitiveness and has significant socio-economic ripple effects throughout the country. However, road construction projects are vulnerable to various risks and prone to cost overruns because they are funded by large-scale national budgets and conducted over long time periods. Therefore, tracking the changes in construction costs from planning to completion and providing insights for similar future projects is essential for successful project planning and management. Considering the bidding conditions and project characteristics of road construction projects, this study comparatively analyzed the construction cost growth of 170 road construction projects based on the bid award rate and facility-specific project characteristics, such as construction type, contract method, facility capacity, and construction cost components. This study analyzed the differences in cost performance between various sample groups using non-parametric tests (Mann–Whitney U test and Kruskal–Wallis test), considering the non-normality of the collected sample. In addition, this study conducted multiple regression analysis to examine the causal relationship between all variables used in the analysis and cost performance and to identify critical factors. The results indicated that the construction cost growth of the group with a bid award rate of less than 70% was higher compared to that of other groups. Furthermore, the differences in construction cost growth based on project characteristics were more pronounced in the following groups: construction types (expansion/renovation and complex), contract method (long-term continuous), road length (≥7.5 km), % of bridge/tunnel length (<10%), construction cost (≤USD 100 mil.), % of direct construction cost (≥70%), and % of bridge/tunnel cost (both less and more than 50%). Furthermore, the regression model showed that % of direct construction cost, bid award rate, total road length, and contract method were shown to be critical factors in construction cost growth, which implies the importance of indirect cost management, PDS selection decisions that affect bid award rates, and risk management for complex projects from the perspective of construction cost growth management. These results empirically demonstrate that bidding conditions and project characteristics are key to understanding the pattern of construction cost growth in road construction projects. Hence, this study provides significant references that can be used by policy makers and clients to estimate cost buffers for future road projects.

SustainabilityVol. 16(22)
Korea Institute of Civil Engineering and Building Technology (KR)
Korea Institute of Construction Technology
Openalex Percentile: Top 33%
BIM and Construction Integration
0.53
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