Publications / 2019 Proceedings of the 36th ISARC, Banff, Alberta, Canada

Development of Classification Model for the Level of Bid Price Volatility of Public Construction Project Focused on Analysis of Pre-Bid Clarification Document

Yeeun Jang, June Seong Yi, Jeongwook Son and Jeehee Lee
Pages 1245-1253 (2019 Proceedings of the 36th ISARC, Banff, Alberta, Canada, ISBN 978-952-69524-0-6)
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.

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