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News
May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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Network Strategies of Hospitality Companies in Emerging and Transitory Economies: Evidence from Russia

P. 519–546.
Sheresheva M. Y., Balaeva O., Predvoditeleva M., Tretyak O., Burnatseva E.

This chapter sheds light on network organisational forms—hotel chains—actively implemented in hospitality services. The concepts of networks are critically analysed and applied to explorative case studies of hotel chains operating in Russia. The chapter adds to the literature in the hospitality industry by expanding on existing theories of network strategies and illustrates their different patterns within the framework of modern hotel chains’ strategies. A detailed description of the current Russian hotel market situation is presented. The main trends in the Russian hospitality sector are analyzed and key factors stimulating the development of Russian hospitality are outlined. The huge potential of the Russian hospitality sector is revealed. Among the factors impeding the future development of the market, the following are identified: the lack of a developed service standards system and the lack of developed marketing policies and strategies (i.e. inefficient pricing, sales, and communication policy; lag in modern technologies). The formation of domestic and international hotel chains in this environment is described. The chapter focuses on the strategies of domestic and international hotel chains operating in the Russian market. Within this theoretical framework and using the current market situation, the strategies of domestic and international hotel chains are differentiated and classified.

Language: English
Full text
Keywords: стратегииРоссиясетевые формы организацииRussiastrategyserviceshotel chainshotel networksгостиничные сети

In book

Service Science Research, Strategy and Innovation: Dynamic Knowledge Management Methods
Service Science Research, Strategy and Innovation: Dynamic Knowledge Management Methods
Hershey: IGI Global, 2012.
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