Model of Knowledge Localization Network Formation and Growth

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Regarding the continuing concentration of economic resources in a limited number of cities, the problem is elaborating economic-mathematical models that consider territorial features. One of the promising objects of modeling is a city’s knowledge accumulation or knowledge localization. The paper proposes to study the patterns of knowledge localization through the construction of research groups that together form a single city network. Existing models of growing networks used to analyze scientific interaction networks are not appropriate for disconnected graphs of a relatively small size and do not capture the features of the city scale. To explain the mechanism of network formation and growth, the methodology of game theory is used. The goal of each researcher is to maximize the individual knowledge change and the joint knowledge volume, realized in two parallel games. As a result of strategic interaction, two equilibria sets are formed, the intersection or union of which explains the nature of one-step group growth. The knowledge localization network development is faced with uncertainty in the number of new researchers and the level of their individual knowledge. The paper shows that both factors can be quantitatively linked to the city scale, thereby differentiating the research groups’ growth duration, as well as the increase in their number.

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Game theory, knowledge localization, set, city, research group, economic-mathematical model

Короткий адрес: https://sciup.org/149149314

IDR: 149149314   |   УДК: 330.42:332.1   |   DOI: 10.15688/ek.jvolsu.2025.2.1