Potential AI-Driven Algorithmic Collusion and Influential Factors in Construction Bidding-Reference-Cited by-同舟云学术

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Potential AI-Driven Algorithmic Collusion and Influential Factors in Construction Bidding

Published:2024-07 Issue:4 Volume:38 Page:
ISSN:0887-3801
Container-title:Journal of Computing in Civil Engineering
language:en
Short-container-title:J. Comput. Civ. Eng.

Author:

Heo Chan¹,Park Moonseo²,Ahn Changbum R.³^ORCID

Affiliation:

1. Ph.D. Student, Dept. of Architecture and Architectural Engineering, Seoul National Univ., Seoul 08826, Republic of Korea.

2. Professor, Dept. of Architecture and Architectural Engineering, Seoul National Univ., Seoul 08826, Republic of Korea.

3. Associate Professor, Dept. of Architecture and Architectural Engineering, Seoul National Univ., Seoul 08826, Republic of Korea (corresponding author). ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Link

https://ascelibrary.org/doi/pdf/10.1061/JCCEE5.CPENG-5683

Reference40 articles.

1. Construction Bidding Markup Estimation Using a Multistage Decision Theory Approach

2. Ahmed, M. O., I. El-adaway, K. Coatney, and M. S. Eid. 2015a. Multi-stage bidding for construction contracts: A game theory approach. Vancouver, BC, Canada: Univ. of British Columbia.

3. An integrated game-theoretic and reinforcement learning modeling for multi-stage construction and infrastructure bidding

4. Solving the Negative Earnings Dilemma of Multistage Bidding in Public Construction and Infrastructure Projects: A Game Theory–Based Approach

5. Construction Bidding and the Winner’s Curse: Game Theory Approach

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