Preventing Adverse Selection Risk of Construction Project Based on Signaling
Author(s): |
Pengcheng Xiang
Xiangnan Song |
---|---|
Medium: | journal article |
Language(s): | English |
Published in: | The Open Construction and Building Technology Journal, December 2014, n. 1, v. 8 |
Page(s): | 439-443 |
DOI: | 10.2174/1874836801408010439 |
Abstract: |
In the construction market, the adverse selection is very prone to occur as a result of the current situation that the two parties’ information is asymmetric, which causes the construction market disorder and uncontrolled market behaviors. For example, in the bidding phase of the project, the owner doesn’t know clearly of the contractor's technical strength, level of management, service quality, and so on; also the contractor is unclear of the owner’s intention of building, financial capacity, and business reputation etc. at the same time, which leads to adverse selection of bidding market because of inaccurate judgment of the actual risk situation and strength of the contractor. In order to preventing this construction project risk,this paper is to apply asymmetric information theory to project risk management and finally proves that the contractor 's strength can become the deferent signal of the risk type of the contractor through the analysis of the signaling model based on the contractor’s strength. Meanwhile, the owner can judge the risk type of the contractor by acquired the strength and pretended cost of bidding. It is helpful to solve the problem of adverse selection by founding an effective mechanism of signaling, thereby preventing construction project risk. |
Copyright: | © 2014 Pengcheng Xiang, Xiangnan Song |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
0.84 MB
- About this
data sheet - Reference-ID
10384220 - Published on:
23/11/2019 - Last updated on:
02/06/2021