Development of classification model for the level of bid price volatility of public construction project focused on analysis of Pre-Bid clarification document

Y. E. Jang, J. S. Yi, J. W. Son, H. B. Kang, J. Lee

Research output: Contribution to conferencePaperpeer-review

1 Scopus citations

Abstract

The purpose of this paper is to classify the level of formation of the bid price by using the type of uncertainty inherent in the bid document as a variable. To this end, the research examined the factors of the project related to the bid price presented in the previous study. Next, the pre-bid clarification document, which can be used to check the uncertainty of the bid documents, is used as a surrogate variable. Through these input variables, this research implemented two kinds of models using four algorithms: one predicts the level of bid price with uncertainty of bid document and the other predicts the level of bid price without uncertainty of bid documents. As a result, the model that predicts the level of the bid price reflecting the uncertainty of the bid document shows about 24 percent better performance than the model that predicts the bid price without reflecting the uncertainty of the bid document.

Original languageEnglish
Pages1245-1253
Number of pages9
StatePublished - 2019
Event36th International Symposium on Automation and Robotics in Construction, ISARC 2019 - Banff, Canada
Duration: 21 May 201924 May 2019

Conference

Conference36th International Symposium on Automation and Robotics in Construction, ISARC 2019
Country/TerritoryCanada
CityBanff
Period21/05/1924/05/19

Keywords

  • Bid Price Average
  • Bid Price Range
  • Bid Price Risk
  • Bid Price Volatility
  • Classification Model
  • Machine Learning (ML)
  • Pre-Bid Clarification
  • Public Construction Project
  • Risk Management
  • Uncertainty of Bid Document

Fingerprint

Dive into the research topics of 'Development of classification model for the level of bid price volatility of public construction project focused on analysis of Pre-Bid clarification document'. Together they form a unique fingerprint.

Cite this