Enhancing Reliability of Construction Contingency Estimation at the Scoping Phase through Historical Cost Data Analysis

被引:0
|
作者
Ko, Taewoo [1 ]
Le, Chau [2 ]
Jeong, H. David [3 ]
Choi, Kunhee [3 ]
机构
[1] Texas A&M Univ Commerce, Dept Engn & Technol, Commerce, TX 75428 USA
[2] Univ North Carolina Charlotte, Dept Engn Technol & Construct Management, Charlotte, NC 28223 USA
[3] Texas A&M Univ, Dept Construct Sci, College Stn, TX 77843 USA
关键词
PROJECTS; MODEL; MANAGEMENT; BUDGET;
D O I
10.1061/AJRUA6.RUENG-1260
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Accurate estimates of construction contingency, a vital element that accounts for unforeseen additional expenses during building, are crucial for construction project agencies. In the initial planning phase, with project specifics still under development, the top-down method is a popular approach for estimating contingency. This method employs a straightforward approach to calculating contingency, using a fixed percentage or a sliding scale based on project variables. While such a method offers simplicity, it suffers from constraints, notably the absence of rigorous evaluation and the challenges of considering project-specific risks. Hence, this research conducts a comprehensive analysis of historical highway project cost performance data to refine the applicability of the sliding scale methodologies and strengthen current top-down approaches. Using various statistical methods, the study creates probability distribution curves that show the likelihood of different contingency costs occurring, along with their associated confidence levels. These probability distribution curves provide cost estimators and project managers with a reliable way to improve the accuracy of early cost estimates during critical planning phases. This study will benefit project agencies by providing a more accurate and informed approach to budgeting and contingency management, thereby improving project cost reliability.
引用
收藏
页数:12
相关论文
共 50 条
  • [31] Cleaning historical maintenance work order data for reliability analysis
    Hodkiewicz, Melinda
    Ho, Mark Tien-Wei
    JOURNAL OF QUALITY IN MAINTENANCE ENGINEERING, 2016, 22 (02) : 146 - 163
  • [32] Traffic Condition Estimation Based on Historical Data Analysis
    Ha Mai Tan
    Hoang-Nam Pham-Nguyen
    Quang Tran Minh
    Phat Nguyen Huu
    IEEE ICCE 2020: 2020 IEEE EIGHTH INTERNATIONAL CONFERENCE ON COMMUNICATIONS AND ELECTRONICS (ICCE), 2021, : 256 - 261
  • [33] Analysis of Historical Transformer Failure and Maintenance Data for Facility Reliability
    Stringer, A. D.
    Thompson, C. C.
    Barriga, C., I
    2019 IEEE/IAS 55TH INDUSTRIAL AND COMMERCIAL POWER SYSTEMS TECHNICAL CONFERENCE (I&CPS), 2019, : 215 - 222
  • [34] Reliability and risk analysis data base development: an historical perspective
    Fragola, Joseph R.
    Reliability Engineering and System Safety, 51 (02): : 125 - 136
  • [35] Analysis of social cost during project construction phase
    Deng, XP
    Li, QM
    Shen, LF
    PROCEEDINGS OF CRIOCM 2005 INTERNATIONAL RESEARCH SYMPOSIUM ON ADVANCEMENT OF CONSTRUCTION MANAGEMENT AND REAL ESTATE, 2005, : 570 - 574
  • [36] Enhancing InSAR Coherence Estimation Through Local Phase Surface Modeling
    Lei, Baocheng
    Zhang, Lei
    Wu, Jicang
    Lu, Zhong
    Liang, Hongyu
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2023, 20 : 1 - 5
  • [37] Supervised data analysis and reliability estimation with exemplary application for spectral data
    Schleif, Frank-Michael
    Villmann, Thomas
    Ongyerth, Matthias
    NEUROCOMPUTING, 2009, 72 (16-18) : 3590 - 3601
  • [38] Enhancing the reliability of hydrological simulations through global weather data assimilation in watersheds with limited data
    Jayaprathiga, Mahalingam
    Rohith, A. N.
    Cibin, Raj
    Sudheer, K. P.
    STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2024, 38 (09) : 3445 - 3459
  • [39] DESIGN ANALYSIS THROUGH TECHNIQUES OF PARAMETRIC COST ESTIMATION
    DASCHBACH, JM
    APGAR, H
    ENGINEERING COSTS AND PRODUCTION ECONOMICS, 1988, 14 (02): : 87 - 93
  • [40] Enhancing the Reliability of IoT Data Marketplaces through Security Validation of IoT Devices
    Na, Yoonjong
    Joo, Yejin
    Lee, Heejo
    Zhao, Xiangchen
    Sajan, Kurian Karyakulam
    Ramachandran, Gowri
    Krishnamachari, Bhaskar
    16TH ANNUAL INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING IN SENSOR SYSTEMS (DCOSS 2020), 2020, : 265 - 272