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, 30(2), pp. 598-622. ISSN 0969-9988
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.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | data-driven; multi-criteria decision-making; project procurement; topsis; unbalanced bidding |
| Index terms: | competitive bidding, identification method, multi-criteria decision-making, accuracy, methodology, decision-making, project procurement, bidding, unbalanced bidding, database, bid evaluation, topsis, owner, decision-making process, best value, fairness, construction industry |
| Subjects: | research methods, tendering, professional development, data management, decision analysis, sociology, leadership, decision-making and optimization, industry analysis, bidding, contractual arrangements, data analysis and analytics |
| Topics: | Research Practice, Information Management, Risk Management, Stakeholder Management, Procurement, Digital Applications, Organizational Design |
| Descriptive scope: | 3 PCT |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here