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News
September 25, 2026
AI Users Earn Up to 41.8% More Than Non-Users
Research conducted by economists at HSE University has revealed a significant correlation between the regular use of GenAI in the workplace and higher pay among Russian employees. The study found that individuals who frequently use GenAI in their professional activities earn notably more than those who reject these new tools or resort to them occasionally. The salary premium for highly qualified specialists reaches 41.8%. The article was published in the Voprosy Ekonomiki journal.
September 24, 2026
‘Feedback and Constructive Criticism Are Essential in Our Profession
Vincent Fardeau, Associate Professor at HSE ICEF, has reached a major career milestone: he recently published his paper ‘Asymmetric Thin Markets’ in the Journal of Financial Economics, successfully passed his major academic review, and received tenure. In this interview, Vincent discusses the story behind the paper, explains the concept of asymmetric thin markets, and shares his advice for young scholars aiming to publish in top-tier journals.
September 22, 2026
Personal Interest in Doctoral Thesis Topic Most Important for Confidence in Successful Defence
A researcher at HSE University analysed data on 1,539 doctoral students from 161 Russian universities to identify which features of a thesis topic are associated with academic success and engagement. The most important factor was found to be personal interest in the research topic, which was associated with almost all key aspects of doctoral programme experience—from engaging with the academic supervisor to research activity and confidence about successfully defending the thesis. The findings have been published in Higher Education.

 

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Прогнозирование численности клиентской базы компании на основе марковских цепей

Экономика и математические методы. 2016. Т. 52. № 1. С. 79–94.
Андреева А. В., Т. К. Богданова

The article represents the information and logical complex model to manage the company’s customer base in order to calculate the index of long-term value of the client. In contrast to the previous issues this model takes into account the peculiarities of consumer behavior and socio–demographic characteristics of the client groups, and the movement of customers within the customer base is represented as a Markov chain. Developed complex dynamic model to manage the company’s customer base makes possible to forecast the cluster frequency and the client base at all on any period, to analyze the population- change-dynamics of client cluster and to highlight the most important stages in the formation and development of the customer base. On each stage highlighted groups of clients are estimated according to future company’s profit and potential for cross selling of products/services. The estimates allow to calculate the budget for marketing activities on retention of given profit level and to compose the most effective plan of address–directed marketing activities.

Research target: Computer Science Economics and Management
Priority areas: economics management business informatics
Language: Russian
Full text
Text on another site
Keywords: розничная торговляretail tradeMarkov chainдинамическая модельcustomer loyaltyмарковские цепилояльность клиентауправление клиентской базой компаниигруппы клиентовmanagement of customer base of the companygroup of clientsdynamic modellong-term value of the customer baseдолгосрочная стоимость клиентской базы
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