An Empirical Study of Optimized Bidding Strategies Based on Logistic Regression Models

DOI

10.2991/978-94-6463-847-9_25How to use a DOI?

Keywords

Bidding Strategy; Decision Model; Logistic Regression

Abstract

With the increasingly fierce competition in China's construction industry, how to stand out in the bidding process has become a priority issue This paper takes the remaining project of a certain old community renovation as an example, based on the real evaluation data, and uses The logistic regression model to analyze the winning probability of each participating enterprise, and studies the impact of each scoring item on the winning result. The results show that reputation and construction organization design have a significant positive effect on the log odds of winning, while the impact of project management organization score has a significant positive effect on the log odds of winning. The results show that reputation and construction organization design have a significant positive effect on the log odds of winning, while the impact of project management organization score and bid price is relatively weak. Based on the nonlinear probability function derived from the Based on the nonlinear probability function derived from the model, this paper proposes optimization strategies for these key factors, aiming to provide a theoretical basis for enterprises to improve their winning probability in the fierce market competition.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yu Yang
AU  - Yali Zhu
AU  - Zhaojuan Wang
AU  - Xinrui Yang
AU  - Siyi Hu
PY  - 2025
DA  - 2025/09/23
TI  - An Empirical Study of Optimized Bidding Strategies Based on Logistic Regression Models
BT  - Proceedings of the 2025 6th International Conference on Urban Construction and Management Engineering (ICUCME 2025)
PB  - Atlantis Press
SP  - 228
EP  - 236
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-847-9_25
DO  - 10.2991/978-94-6463-847-9_25
ID  - Yang2025
ER  -