HSE Researchers Provide the World’s First Legal Definition of a Digital Ecosystem
Digital ecosystems have evolved from a technological innovation into a fundamental institution of the modern economy over the past few years. According to HSE University’s latest estimates, they account for 8.5% of Russia’s GDP. Previously, no jurisdiction had a statutory definition of what constitutes a digital ecosystem. HSE University researchers have addressed this gap by proposing the first legal concept of a digital ecosystem. Their article, ‘The Digital Ecosystem as a Novel Economic Phenomenon and Legal Concept,’ has been published in the BRICS Law Journal.
The study’s authors—Yaroslav Kuzminov, Alexey Koshel, Ekaterina Kruchinskaia, and Salambek Dombaev—are the first to formulate five operational characteristics of a digital ecosystem that are suitable for legal codification. These include the use of technologies and algorithms; the presence of two or more product or service categories; multiple legal entities operating as a corporate group or through contractual partnerships; a single consolidated user database; and the creation of additional consumer value through participation in the ecosystem.
Together, these five characteristics define the core sources of value that digital ecosystems both create and capture: technologies that enable seamless interaction; data that underpins analysis of user behaviour; and simplified user experience and consumer choice resulting from the combination of these two elements.
On this basis, the researchers propose a legal definition of a digital ecosystem: a digital platform, or a set of technologically and organisationally interconnected digital platforms, that enables users to obtain additional consumer value when purchasing goods, works, or services within the ecosystem through the use of a consolidated user database, technological and organisational solutions.
Organisational solutions include a unified authentication system and a single system of bonuses and customer preferences, while technological solutions consist of algorithms that simplify consumer choice and reduce the time or costs associated with making purchases compared with buying the same goods or services outside the ecosystem.
From an economic perspective, a digital ecosystem performs an infrastructural function by providing participants with access to a shared database, unified interfaces, and standardised rules of interaction. This dramatically reduces transaction costs and generates network effects for all participants. The proposed definition also draws, for the first time, a clear distinction between a digital ecosystem and related phenomena. A sophisticated digital platform is essentially a technological aggregation of services typically operated by a single legal entity. A digital ecosystem, by contrast, consists of multiple legally or organisationally distinct entities—either companies within a corporate group or contractual partners—operating on the basis of a shared infrastructure. This distinction has direct practical implications for determining legal liability, the applicable tax regime, and the scope of antitrust regulation.
In Russia, where digital ecosystems are often built around banks, this distinction is particularly significant. Goods, financial flows, and personal data frequently circulate within the same ecosystem, while personal data may become intertwined with information protected by banking secrecy. Regulators therefore need a clear understanding of the legal nature of the entities involved in each specific case.
The authors note that the Russian experience offers valuable material for the international debate. The integration of financial and non-financial activities through a single consolidated database creates effects that have no direct equivalent in Western models and therefore require a distinct legal framework.
The study also identifies a number of unresolved issues, the most significant of which concerns data rights. Given that data represents the primary source of value in a digital ecosystem, the researchers argue that this issue should be addressed through a constructive and gradual dialogue between digital ecosystems and regulators. The first step should be to determine the value that users derive from a platform’s recommendation capabilities, and only then to begin discussing how platform data should be governed.
Building on the proposed definition and conceptual distinctions, the authors identify five priority areas for the further development of legal regulation: adapting competition law to reflect the specific nature of competition both within and between digital ecosystems; revising consumer protection rules to account for increasingly complex transactional models; developing mechanisms to protect information and personal data when they are consolidated and transferred across borders; establishing flexible tax regimes that reflect the distinctive revenue and cost structures of digital ecosystems; and adapting intellectual property and advertising regulations to the dynamic environment of algorithm-driven content distribution and personalised advertising.
The proposed definition and system of defining characteristics provide a foundation for moving beyond qualitative descriptions of digital ecosystems towards legally meaningful criteria that can be applied in regulatory and judicial practice. This does not mean that all regulatory challenges have been resolved. On the contrary, the authors emphasise that substantial work remains to adapt sector-specific legislation. However, this process can now proceed on the basis of a clear understanding of precisely what is to be regulated.
See also:
‘The Peak of Stupidity’ and ‘The Valley of Despair’: HSE Economists Propose an Explanation for the Dunning–Kruger Effect
The Dunning–Kruger effect, which describes a sharp surge in self-confidence among beginners followed by an equally rapid decline as they gain experience, can be explained by the nature of the learning process and the acquisition of new knowledge. This conclusion was reached by Andrey Vorchik of the HSE Faculty of Economic Sciences together with independent researcher Murat Mamyshev. They developed a mathematical model of learning and demonstrated how subjective confidence is formed and changes as knowledge accumulates, as well as how teachers can reduce the ‘valley of despair’ experienced by learners.
Toffee and Risk: Scientists Discover Why People Who Crave Sweets Make More Impulsive Choices
Having a sweet tooth may be linked not only to eating habits but also to the way people make decisions. Researchers at HSE University have found that people with a preference for sweet foods tend to behave more impulsively—not because they want immediate rewards, but because they are less willing to tolerate uncertainty. These findings may help improve treatments for addiction. The study findings have been published in Frontiers in Psychology.
Physicists Find a Way to Model Ion Parameters in Plasma in Seconds
Researchers from HSE University and the Moscow Institute of Physics and Technology (MIPT) have developed a set of simple analytical methods for calculating the properties of heavy ions in helium under the influence of a strong electric field. The new approach speeds up calculations of ion mobility and ion–molecule reaction rates by thousands of times while maintaining sufficient accuracy for plasma jet modelling. The findings have been published in the journal Physica Scripta.
Two Years of Growth or Decline: How to Choose an Investment Strategy
Economists from HSE University, together with colleagues from international universities, have analysed stock market movements over almost a century and proposed an investment strategy that could have delivered returns nearly twice as high as the market average. Their research suggests following a momentum strategy during periods of sustained market growth and switching to a value strategy after prolonged market declines. The study has been published in the Journal of Banking and Finance.
Researchers Reveal Link Between Attention and Communication Difficulties in Autism
Researchers at HSE University have examined how communication difficulties in children with autism are related to brain function. The findings show that not only language networks but also attention networks play an important role. The weaker the connections involved in maintaining focus and switching attention, the more pronounced communication difficulties were. The study has been published in European Child & Adolescent Psychiatry.
Scientists Discover Why Some People Wore Masks During COVID-19 While Others Did Not
Why do some people voluntarily follow new rules while others ignore them? Researchers at HSE University have found that the answer lies not so much in people's willingness to cooperate, as previously believed, but in their ability to empathise with others. Empathy proved to be the strongest predictor of whether people chose to wear face masks voluntarily during the COVID-19 pandemic. The findings have been published in Frontiers.
Physicists at HSE University and FIAN Discover Way to 'Photograph' Sound for Testing Materials Used in 6G Communications
Researchers at HSE University, in collaboration with colleagues from the Lebedev Physical Institute of the Russian Academy of Sciences (FIAN), have developed a method for rapidly determining how firmly a film is bonded to a substrate. This is important for the creation of ultrahigh-frequency acoustic filters, which are key components of next-generation 5G and 6G communications. For the first time, researchers have succeeded in measuring the lateral rigidity of the bond between a two-dimensional material film and a substrate in this way. The study results have been published in Applied Physics Letters.
Scientists Create Open Dataset for Studying Concentration
A team of Russian researchers, including scientists from HSE University–St Petersburg, has developed the first open multimodal dataset containing recordings of brain activity, heart function, and video observations to help researchers understand what happens in the human brain during deep concentration. In the future, the dataset could accelerate the development of neural interfaces, rehabilitation technologies, and AI systems. The article has been published in Scientific Data.
Scientists Propose Method for More Efficient Resource Use in Machine Learning
An international group of researchers, including mathematicians from the AI and Digital Science Institute at the HSE Faculty of Computer Science, has provided a theoretical justification for a simple and computationally efficient method of estimating uncertainty in Stochastic Gradient Descent (SGD). The paper has been published on the scientific preprint server arXiv.org and presented at AISTATS 2026.
Team Success: Aligning Means with Objectives
In corporations, sports, and academia, people often face challenges they cannot handle alone. In such cases, selecting the right team is crucial. Tatiana Mayskaya, Associate Professor at the HSE Faculty of Economic Sciences and the International College of Economics and Finance, together with colleagues from foreign universities, examined team characteristics and found that less diverse teams are better suited to objectives where a high average performance is important, whereas more diverse teams are preferable when avoiding failure is critical. The paper has been published in Economic Theory.