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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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The use of readiness assessment for big data projects

Sustainable Cities and Society. 2020. Vol. 60. Article 102233.
Barham H., Daim T.

Big data projects, including smart-city-related big data projects, are facing an alarmingly high percentage of failure. The reasons behind this phenomenon and the lessons learned from it are well researched. However, big data projects are still failing, as there is a lack of effective models to leverage the lessons learned from previous projects to evaluate an organization’s readiness for a big data project.

In this paper, the authors introduce a novel readiness assessment model. This model leverages the lessons learned from previous projects and the experience of experts to be better prepared for an upcoming smart-city-related big data project. Cities can use the model to evaluate their readiness for this type of project in a structured and comprehensive way that will allow for higher chances of conducting a successful big data project.

To develop the model, hierarchical decision modeling (HDM) and expert judgment quantification were used to provide the categorization and relative ranking of factors that influence smart-city-related big data projects. HDM is an effective way to understand the relationship between multiple factors and allows for expert panels to prioritize those factors. Moreover, desirability functions were used to extend the understanding of the factors’ dynamics and what needs to be done to better prepare for the challenges associated with each factor. Finally, the model was tested by applying it to several smart-city-related big data projects to show its value.

This research highlights the importance of readiness assessment for conducting big data projects and provides a readiness assessment model that cities can use to prepare for an upcoming big data project.

Research target: Computer Science
Priority areas: management
Language: English
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Keywords: большие данныеtechnology managementуправление технологиямиBig data projects
Publication based on the results of:
The impact of science, technology, and innovation on structural transformation (2020)
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