The framework of data-driven and multi-criteria decision-making for detecting unbalanced bidding
Engineering, Construction and Architectural Management
ISSN: 0969-9988
Article publication date: 2 November 2021
Issue publication date: 14 March 2023
Abstract
Purpose
Unbalanced bidding can seriously imposed the government from obtaining the best value for the taxpayers' money in public procurement since it increases the owner's cost and decreases the fairness of the competitive bidding process. How to detect an unbalanced bid is a challenging task faced by theoretical researchers and practical actors. This study aims to develop an identification method of unbalanced bidding in the construction industry.
Design/methodology/approach
The identification of unbalanced bidding is considered as a multi-criteria decision-making (MCDM) problem. A data-driven unit price database from the historical bidding document is built to present the reference unit prices as benchmarks. According to the proposed extended TOPSIS method, the data-driven unit price is chosen as the positive ideal solution, and the unit price that has the furthest absolute distance measure as the negative ideal solution. The concept of relative distance is introduced to measure the distances between positive and negative ideal solutions and each bidding unit price. The unbalanced bidding degree is ranked by means of relative distance.
Findings
The proposed model can be used for the quantitative evaluation of unbalanced bidding from a decision-making perspective. The identification process is developed according to the decision-making process. The finding shows that the model will support owners to efficiently and effectively identify unbalanced bidding in the bid evaluation stage.
Originality/value
The data-driven reference unit prices improve the accuracy of the benchmark to evaluate the unbalanced bidding. The extended TOPSIS model is applied to identify unbalanced bidding; the owners can undertake objective decision-making to identify and prevent unbalanced bidding at the stage of procurement.
Keywords
Acknowledgements
The authors acknowledge with gratitude the MOE (Ministry of Education in China) Project of Humanities and Social Sciences (No. 19YJC630078); National Key R&D Program of China (No. 2018YFC0406905); Youth Talents Teachers Scheme of Henan Province Universities (No. 2018GGJS080), the National Natural Science Foundation of China (Nos. 71974056 and 71302191), the Foundation for Distinguished Young Talents in Higher Education of Henan (Humanities & Social Sciences), China (No. 2017-cxrc-023), China Scholarship Council (No. 201908410388), 2018 2021 Key R & D and Promotion Special Project of Henan Province (Tackling Key Science and Technology) (212102310392). This study would not have been possible without their financial support.
Data availability: The data used to support the findings of this study are available from the corresponding author upon request.
Conflict of interest: The authors declare that they have no conflict of interest.
Citation
Li, H., Su, L., Zuo, J., An, X., Dong, G., Wang, L. and Zhang, C. (2023), "The framework of data-driven and multi-criteria decision-making for detecting unbalanced bidding", Engineering, Construction and Architectural Management, Vol. 30 No. 2, pp. 598-622. https://doi.org/10.1108/ECAM-08-2020-0603
Publisher
:Emerald Publishing Limited
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