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October 8, 2026
HSE Experts Take Part in 23rd Annual Meeting of Valdai Discussion Club
The 23rd Annual Meeting of the Valdai Discussion Club was held from September 28 to October 1, 2026 under the theme ‘Responsibility for the Future: Limits of the Possible, or Limitless Possibilities?’ The forum brought together 120 experts from 40 countries, including representatives of China, the United States, India, Brazil, the United Kingdom, Germany, Egypt, Iran, and Japan.
October 7, 2026
‘Our Team Consists of True Leaders in Their Respective Academic Disciplines
The HSE International Centre of Decision Choice and Analysis studies a wide range of methods for analysing decision-making and possible scenarios for the development of natural, socio-economic, and political phenomena using various mathematical models. The application of advanced mathematical methods to forecasting helps to prevent negative outcomes and avoid erroneous decisions. The HSE News Service spoke to the centre’s director, Prof. Fuad Aleskerov, about its work.
October 6, 2026
International N5 Symposium ‘Neural Networks and Nonlinearity in Nizhny Novgorod Brings Together Scientists from Russia and Serbia
The International N5 Symposium ‘Neural Networks and Nonlinearity in Nizhny Novgorod’ was held at the Nizhny Novgorod House of Scientists from September 23 to 26. The event was organised by HSE University–Nizhny Novgorod and the Nizhny Novgorod House of Scientists, with the participation of Sberbank and the Institute of Physics Belgrade. The symposium was held for the second time: the first conference took place in 2025 and attracted considerable interest from the academic community.

 

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Agent-Based Modeling of Construction Firms’ Organizational Behavior in Public Tenders

Journal of Risk and Financial Management. 2023. Vol. 16. No. 2. Article 105.
Gladkikh V., Alekseev A.

A key problem of construction firms’ management and economy is organization of effective participation in public tenders. The direct executor, who determines the price of the contract, may be interested in obtaining as many contracts as possible. It means that his strategic behavior in tender may be to undervalue each individual offer. At the same time, such a strategy can be a source of risk of project loss because the actual costs may be lower than the price of the contract won. The management of the construction organization is not interested in this. On the other hand, overpricing strategy may lead to a reduction in the number of contracts won, which may not seem effective either for the head or for the executor of such an organization. The article discusses whether the profits of a construction firm can increase by using a more precise method of calculating the estimated cost. The second question is—which staff of a construction firm will benefit from using such methods? The aim of this work is to test these hypotheses with the instrumentality of agent-based modeling. Profit values of construction firms were obtained by the computer simulation of the construction firms’ strategic behavior in public tenders. Results of 1500 computer experiments are presented as a decision tree. It can be seen that when using a more precise method, construction firms win tenders almost two times less often. However, they incur losses many times less than with an inaccurate method. If a construction firm made a profit from the contracts won, the profit margin was almost always greater when using the more precise method. Moreover, the results of game-theoretic modeling are given. Values of the objective functions of the executor and head of the construction firm were obtained, taking into account the reward for contracts won and penalty for miscalculating the cost of work. It has been proved that using more precise methods for calculating the estimated cost is beneficial to both the head and the executor. It can be concluded that both hypotheses were confirmed and a precise method for calculating the cost increases the efficiency of a construction firm.

Research target: Computer Science Economics and Management
Language: English
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Keywords: Agent-based modeling and simulation
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