Data Mining Framework to Optimize the Bid Selection Policy for Competitively Bid Highway Construction Projects-Reference-Cited by-同舟云学术

Data Mining Framework to Optimize the Bid Selection Policy for Competitively Bid Highway Construction Projects

Published:2012-02 Issue:2 Volume:138 Page:277-286
ISSN:0733-9364
Container-title:Journal of Construction Engineering and Management
language:en
Short-container-title:J. Constr. Eng. Manage.

Author:

Art Chaovalitwongse W.¹²³⁴,Wang Wanbin¹²³⁴,Williams Trefor P.¹²³⁴,Chaovalitwongse Paveena¹²³⁴

Affiliation:

1. Associate Professor, Dept. of Industrial and Systems Engineering, Rutgers Univ. 96 Frelinghuysen Rd, Piscataway, NJ 08854.Visiting Associate Professor, Dept. of Operations Research and Financial Engineering, Princeton Univ. Sherrerd Hall, Charlton Street, Princeton, NJ 08544.Affiliate Associate Professor, Dept. of Industrial and Systems Engineering, Univ. of Washington, 3900 Stevens Way, Seattle, WA 98195.

2. Graduate Assistant, Dept. of Industrial and Systems Engineering, Rutgers Univ., 96 Frelinghuysen Rd, Piscataway, NJ 08854.

3. Professor, Dept. of Civil and Environmental Engineering, Rutgers Univ., 623 Bowser Rd, Piscataway, NJ 08854 (corresponding author).

4. Assistant Professor, Dept. of Industrial Engineering, Chulalongkorn Univ., Phayathai Rd, Bangkok, 10330, Thailand.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Strategy and Management,Industrial relations,Building and Construction,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CO.1943-7862.0000386

Reference26 articles.

1. Key Factors in Bid Reasoning Model

2. Case-Based Reasoning Approach in Bid Decision Making

3. Testing Vickery’s Revenue Equivalence Theory in Construction Auctions

4. Classifying Construction Contractors Using Unsupervised-Learning Neural Networks

Cited by 30 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Potential AI-Driven Algorithmic Collusion and Influential Factors in Construction Bidding;Journal of Computing in Civil Engineering;2024-07

2. Comprehensive Understanding of Factors Impacting Competitive Construction Bidding;Journal of Construction Engineering and Management;2024-04

3. Predicting the Number of Bidders in Construction Competitive Bidding Using Explainable Machine Learning Models;2024

4. Application of subcontracting as a quality improvement tool for building constructions in Sri Lanka;International Journal of Construction Management;2023-05-10

5. Does Competition Impact Workplace Safety in Public Utilities' Procurement? Insights From Bid-Estimate Ratio and Firm Size;IEEE Transactions on Engineering Management;2023