Geographic Information System–Based Framework for Estimating and Visualizing Unit Prices of Highway Work Items

Le, Chau; Le, Tuyen; Jeong, H. David

doi:10.1061/(asce)co.1943-7862.0001672

Cited by 11 publications

(7 citation statements)

References 46 publications

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“…The cost of new construction projects is different from that of rebuilding projects because each type of project requires a distinct approach to construction. Additionally, as the unit price varies across various bid items varies often, the best strategies for two distinct bid items could not be the same (Le et al ., 2019).…”

Section: Resultsmentioning

confidence: 99%

“…However, the subjectivity and randomness associated with using modeling techniques and tools to estimate construction costs have been criticized because such randomness is intrinsic in the construction industry (Hassanein, 2006). Several researchers have conducted studies to improve the estimation process, including the use of geographic information systems to estimate highway construction bid items (Martinez, 2010; Zhang, 2010; Shrestha and Shrestha, 2014; Le et al ., 2019). Other researchers also applied ANNs, case-based reasoning (CBR), GA and RA to enhance the cost estimation process (Adeli and Wu, 1998; Hegazy and Ayed, 1998; Al-Tabtabai et al ., 1999; Chou, 2009a; Kim and Kim, 2010; Cirilovic et al ., 2014; Adel et al ., 2016; Meharie et al.…”

Section: Introductionmentioning

confidence: 99%

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Conceptual cost estimation of highway bid items – A systematic literature review

Awuku

Asa

Baffoe-Twum

et al. 2022

ECAM

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PurposeChallenges associated with ensuring the accuracy and reliability of cost estimation of highway construction bid items are of significant interest to state highway transportation agencies. Even with the existing research undertaken on the subject, the problem of inaccurate estimation of highway bid items still exists. This paper aims to assess the accuracy of the cost estimation methods employed in the selected studies to provide insights into how well they perform empirically. Additionally, this research seeks to identify, synthesize and assess the impact of the factors affecting highway unit prices because they affect the total cost of highway construction costs.Design/methodology/approachThis paper systematically searched, selected and reviewed 105 papers from Scopus, Google Scholar, American Society of Civil Engineers (ASCE), Transportation Research Board (TRB) and Science Direct (SD) on conceptual cost estimation of highway bid items. This study used content and nonparametric statistical analyses to determine research trends, identify, categorize the factors influencing highway unit prices and assess the combined performance of conceptual cost prediction models.FindingsFindings from the trend analysis showed that between 1983 and 2019 North America, Asia, Europe and the Middle East contributed the most to improving highway cost estimation research. Aggregating the quantitative results and weighting the findings using each study's sample size revealed that the average error between the actual and the estimated project costs of Monte-Carlo simulation models (5.49%) performed better compared to the Bayesian model (5.95%), support vector machines (6.03%), case-based reasoning (11.69%), artificial neural networks (12.62%) and regression models (13.96%). This paper identified 41 factors and was grouped into three categories, namely: (1) factors relating to project characteristics; (2) organizational factors and (3) estimate factors based on the common classification used in the selected papers. The mean ranking analysis showed that most of the selected papers used project-specific factors more when estimating highway construction bid items than the other factors.Originality/valueThis paper contributes to the body of knowledge by analyzing and comparing the performance of highway cost estimation models, identifying and categorizing a comprehensive list of cost drivers to stimulate future studies in improving highway construction cost estimates.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Conceptual cost estimation of highway bid items – A systematic literature review

Awuku

Asa

Baffoe-Twum

et al. 2022

ECAM

View full text Add to dashboard Cite

show abstract

“…Martinez (2010) validated different methods for adjusting construction cost estimates by project location, while Li and Heap (2014) compared spatial interpolation methods applied in the environmental sciences. Others such as Zhang et al (2017) and Le et al (2019) have visually extended the use of such proximity-based techniques via satellite imagery and geographic information systems (GIS). Le et al (2019), used a GIS-based framework to estimate and visualize the prices of highway work Items.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Others such as Zhang et al (2017) and Le et al (2019) have visually extended the use of such proximity-based techniques via satellite imagery and geographic information systems (GIS). Le et al (2019), used a GIS-based framework to estimate and visualize the prices of highway work Items.…”

Section: Literature Reviewmentioning

confidence: 99%

The statistical sensitivity of highway project cost to geo-heterogeneity in the tropics

Amadi

2021

IJBPA

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PurposeThe study is carried out to analytically reconnoiter geotechnical index properties of subgrade soils as key variables that shape the cost profile of road infrastructure projects in a tropical geographic setting with starkly heterogenous ground conditions.Design/methodology/approachUsing the Niger Delta region, as a point of reference, data on geotechnical index properties of subgrade soils at spatially dispersed locations for 61 completed highway projects are collated. Exploratory statistical tests were carried out to infer significant associations with final project costs before regression analysis. Regression analysis is principally deployed as an explanatory analytical tool, relevant to quantify the sensitivity of highway project costs to the individual and collective impact of geotechnical variables.FindingsSeveral parameters of expansivity and compressibility exhibited significantly strong associations with the final costs recorded on the highway projects. The statistical analysis further established a cause-effect relationship, whereby small changes in the geotechnical properties of sub-grade soils at project locations, would result in disproportionately large changes in the cost of road construction.Practical implicationsThe study findings provide insight into the sensitivity of road construction costs to geotechnical variables, which can serve as a useful input in financial risk analysis for development appraisal and the generation of location adjustment factors.Originality/valueThe study statistically demonstrates location-induced construction cost profiles, triggered in response to the spatial geotechnical variability and occurrence of problem subgrade soils in the humid tropics, which may be different from those traditionally established in studies of cold and temperate climate soils.

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“…However, the presence of several high peak values caused the di culties in the normal transformation , and the limited sampling points decreased the accuracy of the interpolation in the subregions (Modis et al 2008). A cokriging method with auxiliary variables can be used to obtain relatively accurate spatial distribution information for pollutants (Le et al 2019;Tziachris et al 2017). This is because cokriging method can incorporate both spatial and intervariable correlations into the spatial interpolation (Juang et al 1996).…”

Section: Introductionmentioning

confidence: 99%

Effectiveness of predicting the spatial distributions of target contaminants of a coking plant based on their related pollutants

Qiao

Lai²,

Yang

et al. 2022

Environ Sci Pollut Res

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The prediction accuracy of the spatial distribution of soil pollutants at a site is relatively low. Related pollutants can be used as auxiliary variables to improve the prediction accuracy. However, little relevant research has been conducted on site soil pollution. To analyze the prediction accuracy of target pollutants combined with auxiliary pollutants, Cu, toluene, and phenanthrene were selected as the target pollutants for this study. Based on geostatistical analysis and spatial analysis, the following results were obtained. (1) The reduction rate of the root mean square errors (RMSEs) for Cu, toluene, and phenanthrene with multivariable cokriging were 68.4%, 81.6%, and 81.2%, respectively, which are proportional to the correlation coe cient of the relationship between the auxiliary pollutants and the target pollutants. (2) The predicted results for Cu, phenanthrene, and toluene and their corresponding related pollutants are more accurate than the results obtained not using the related pollutants. (3) In the interpolation process, the RMSEs for Cu, toluene, and phenanthrene with multivariable cokriging basically increase as the neighborhood sample data increases, and then they become stable. (4) When 84, 61, and 34 sample points were removed, the RMSEs for Cu, toluene, and phenanthrene, respectively with multivariable cokriging were close to the RMSEs of the target pollutants based on the total samples. The results are of great signi cance to improving the prediction accuracy of the spatial distribution of soil pollutants at coking plant sites.

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Geographic Information System–Based Framework for Estimating and Visualizing Unit Prices of Highway Work Items

Cited by 11 publications

References 46 publications

Conceptual cost estimation of highway bid items – A systematic literature review

Conceptual cost estimation of highway bid items – A systematic literature review

The statistical sensitivity of highway project cost to geo-heterogeneity in the tropics

Effectiveness of predicting the spatial distributions of target contaminants of a coking plant based on their related pollutants

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