Classifying the Level of Bid Price Volatility Based on Machine Learning with Parameters from Bid Documents as Risk Factors

YeEun Jang, JeongWook Son and June-Seong Yi
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YeEun Jang: Department of Architectural & Urban Systems Engineering, Ewha Womans University, Seoul 03760, Korea
JeongWook Son: Department of Architectural & Urban Systems Engineering, Ewha Womans University, Seoul 03760, Korea
June-Seong Yi: Department of Architectural & Urban Systems Engineering, Ewha Womans University, Seoul 03760, Korea

Sustainability, 2021, vol. 13, issue 7, 1-18

Abstract: The purpose of this study is to classify the bid price volatility level with machine learning and parameters from bid documents as risk factors. To this end, we studied project-oriented risk factors affecting the bid price and pre-bid clarification document as the uncertainty of bid documents through preliminary research. The authors collected Caltrans’s bid summary and pre-bid clarification document from 2011–2018 as data samples. To train the classification model, the data were preprocessed to create a final dataset of 269 projects consisting of input and output parameters. The projects in which the bid inquiries were not resolved in the pre-bid clarification had higher bid averages and bid ranges than the risk-resolved projects. Besides this, regarding the two classification models with neural network (NN) algorithms, Model 2, which included the uncertainty in the bid documents as a parameter, predicted the bid average risk and bid range risk more accurately (52.5% and 72.5%, respectively) than Model 1 (26.4% and 23.3%, respectively). The accuracy of Model 2 was verified with 40 verification test datasets.

Keywords: risk management; risk analysis; bid price volatility; uncertainty in bid documents; pre-bid clarification document; machine learning (ML), classification model; public project; sustainable project management (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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