Published on: 2026-09-30
Source: Saint Petersburg State University of Architecture and Civil Engineering –
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Associate Professor of the Department of Construction Economics and Housing and Communal Services, Candidate of Economic Sciences Yuri Tsvetkov completed a study devoted to reducing information asymmetry in the public construction procurement market through digital technologies. The project was carried out with the support of an internal grant from SPbGASU for conducting research work.
The problem of information asymmetry arises when the government customer cannot fully assess the real potential of the contractor organization. As a result, conscientious companies may lose competitive procedures, and the selection of the contractor does not always minimize risks during the implementation of the construction project.
According to research data, in 2025, 19.4% of government construction contracts were terminated for various reasons, and about 10% of procurements did not take place due to a lack of bids. At the same time, in approximately 80% of cases, the auction winner is determined solely by the lowest price, without a full assessment of their qualifications and capabilities.
How to identify a reliable contractor
As part of the research project, Yuri Tsvetkov analyzed a data set on contracting organizations for 2024. Based on machine learning methods, a predictive model was developed to identify factors affecting the likelihood of successful execution of a government contract.
One of the key indicators was the organization’s profit. In the examined sample, the probability of successful contract execution approaches zero for companies operating at a loss. The average loss among such organizations amounted to 53.8 million rubles. At the same time, the model defines the threshold reliability value as an average profit level of 238.12 million rubles.
Another significant factor turned out to be experience in executing construction projects. The highest probability of successful contract fulfillment was noted among contractors who have implemented an average of 47 projects over the past three years. For organizations with experience in only one project, the probability of success is 10–20%.
Separately, the model takes into account the financial condition of the company. If the organization is in bankruptcy, the probability of contract termination becomes maximal. In the studied sample, 44% of unscrupulous contractors were in bankruptcy.
From price assessment to the contractor’s digital profile
The study systematized theoretical approaches to markets with asymmetric information and examined government regulatory measures applied to increase transparency of such markets. Among them are the Russian “Honest Sign” system and foreign experience in using “Open Banking” technologies.
Three main blocks of systemic problems in the state construction order market were also identified: financial and personnel difficulties of contracting organizations, lack of competencies among public customers, and imperfections in the contract system, including dumping and the formal application of non-price criteria.
Based on the obtained data, a methodology for the preliminary assessment of bidding participants has been developed. It allows forming a digital profile of the organization taking into account not only the proposed price but also financial stability, experience, resource base, reputation, and other characteristics.
The scientific novelty of the work lies in the proposed algorithm for integrating predictive analytics directly into procurement procedures. This approach makes it possible to shift from a primary focus on contract cost to a comprehensive digital assessment of the reliability of a potential contractor.
New opportunities for EIS
The practical significance of the study is related to the possibility of applying the results by government customers and authorities in the field of the contract system.
Yuri Tsvetkov proposes to supplement the Unified Information System in the procurement sphere with new digital modules. One of them is the “Contractors Database” with automatic calculation of a reliability index based on economic indicators, resource availability, experience, reputation, and other characteristics of the organization.
The second module is the “Database of Unclaimed Lots.” It will allow suitable contracts to be offered again to companies that did not pass the main tender but have the necessary potential to fulfill them. This can help reduce the number of failed procurements and more effectively find contractors for complex construction projects.
The proposed model is aimed at a deeper assessment of the qualitative characteristics of bidders and reducing the reliance of the procurement outcome solely on the lowest price. Its application, according to the research results, will help reduce the risks of selecting an unreliable contractor and decrease the number of unfinished construction projects.
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