VR technology is increasingly being integrated into daily life, with virtual book communities emerging as novel platforms for immersive reading and interaction. This study investigates how internal and external factors jointly influence users’ usage intention from psychological and behavioral science perspectives. A multivariate structural equation model based on three-dimensional perception theory was developed and tested through a survey of individuals with prior VR reading experience. The model examines the roles of task–technology fit, privacy and security risks, emotional resonance, self-expression, and the sense of belonging. The results reveal that task–technology fit positively influences usage intention, while privacy and security risk has a negative effect. Internally, emotional resonance and a sense of belonging significantly enhance usage intention. Furthermore, emotional resonance mediates the relationship between self-expression and both sense of belonging and usage intention, while sense of belonging also mediates between emotional resonance and usage intention. These findings underscore the critical interplay between technical attributes and affective factors in shaping engagement with VR-based reading platforms. This study offers new insights into user acceptance mechanisms in virtual book communities, and provides a theoretical foundation and practical implications for enhancing user experience and adoption in digital library systems.

The purpose of this paper is to determine the qualitative features of development and transformation vectors of the information industry of the People’s Republic of China. The methodology. The research was conducted using a set of theoretical and empirical methods of scientific knowledge, which made it possible to identify the main stages in the evolution of the scientific and technical information system of the People’s Republic of China, to establish innovation vectors of its modern development. The following scientific approaches were cognitive tools for the implementation of this goal: systematic, historical, comparative, as well as research methods: statistical, modeling, content analysis of the website of the Institute for Scientific and Technical Information of China. The results. The generalization of the history of the origin and development of the scientific and technical information system of the PRC has identified three main stages of its institutionalization: starting stage (1956–1976), stage of sustainable development (1977–2000), stage of innovation changes (2001–present). At the first stage, a powerful start in the development of an effective state system of scientific and technical information was interrupted by a decade of regressive influence on the socio­economic development of the so­called “cultural revolution”. The second stage was marked by the breakthrough technologies in the implementation of projects for the development of effective tools for searching and systematization of scientific and technical information, in particular, the development of the “Chinese Library Classification” and the “Chinese Subject Thesaurus” in all fields of study, which won the National Prize in Science and Technology in 1983; the creation of the first automated abstract database “Chinese Pharmacy Abstracts” in 1984; the development of unique software for Chinese characters that ran on IBM­class computers, etc. The organizational infrastructure of the national scientific and technical information system was based on a combination of territorial and branch principles, as a result, regional information centers were formed in 27 provinces, municipalities and autonomous regions of the country, as well as departmental ones at large enterprises of 64 ministries of the PRC. The qualitative features of the third stage of development of the Information Industry of China — the stage of innovation changes — identify the processes of digital globalization, automation of Big Data processing, mastering the capabilities and technologies of artificial intelligence in the management of big data and the extraction of explicit and implicit knowledge. The scientific novelty. The author suggests a periodization of the main stages of development of the state system of scientific and technical information of the People’s Republic of China into scientific circulation for the first time; reveals the qualitative features of its functioning at each historical stage; identifies the vectors of diversification of Intelligent Products and Services, transformation strategies for the application of Smart Knowledge Service ecosystems, operated on the basis of analytical processing of big data by artificial intelligence technologies. The practical significance. The experience of developing the information industry and its transformation into the knowledge industry in China is useful to be borrowed by the Ukrainian state scientific and technical information system.

The purpose of this article is to reveal the structure and innovative potential of the big data industry as a component of China’s scientific and technical information system. The methodology. The research was conducted using a complex of theoretical and empirical methods of scientific knowledge, which made it possible to identify the main components of China’s scientific and technical information system, establish its innovative functionality through the identification of the capabilities of national and industry platforms of big data, their aggregators and users. The following scientific approaches were used as a cognitive toolkit for the realization of the set goal: systemic, structural-functional, comparative, as well as research methods: source studying, statistical, modeling, content analysis of the sites of the Documentation and Information Center of the Chinese Academy of Sciences. The results. Summarizing the achievements of the People’s Republic of China in the implementation of the “National Strategy for the Formation of Big Data” made it possible to establish that the key aggregators of this information resource are the Ministry of Industry and Information Technology of the People’s Republic of China, the Center for Documentation and Information of the Chinese Academy of Sciences, the National Center for Innovative Technologies of Engineering Big Data on Earth and Space, the Institute of Aerospace Information Innovations of the Chinese Academy of Sciences, the National Astronomical Observatory of China, the Bureau of Geological Survey of the Ministry of Natural Resources of China, the Institute of Remote Sensing and Digital Earth of the Chinese Academy of Sciences, the Institute of Agricultural Resources and Agricultural Zoning of the Chinese Academy of Agricultural Sciences, which form powerful industrial big data platforms. It is substantiated that the adoption of unified standards and data management protocols and their exchange, guaranteeing data security through the development of powerful technical tools for the protection of digital resources will contribute to increasing the efficiency of the interaction of big data platforms regarding their corporate use. An important organizational measure to accelerate the aggregation and integration of big data is the creation of a national industrial Internet center for big data processing, among the functions of which will be the collection of industrial data, support for their monitoring and analysis, opening of the Center’s resources for small and medium-size enterprises, popularization of the possibilities of corporate application of big data in all aspects of the life cycle of production of products and services as a condition for introducing innovations and increasing business competitiveness. The most effective model of the Center’s work is a multi-level structure that combines the resources of regional and industry sub-centers of industrial and scientific big data, which will ensure their integration and corporate cooperation of big data aggregators on the creation, processing and use of this powerful innovative resource. The scientific novelty. For the first time, an idea of the structure, functionality and technologies of China’s big data industry was introduced into the scientific circulation, the qualitative features and subjects of the aggregation of scientific and industrial big data were identified, their possibilities for the production of intelligent information products and services were determined, tools for the integration of regional and industry resources were proposed platforms of big data, the prospects of corporate processing and use of big data as a strategic resource for the development of the digital economy were outlined. The practical significance. The experience of China’s development of an innovative infrastructure of powerful scientific and industrial big data platforms, which are analyzed using modern cloud technologies, blockchain and artificial intelligence, and its transformation into a knowledge industry is useful for borrowing by the Ukrainian state system of scientific and technical information.

The article aims to study the current level of digital services of the regional subsystem of the National System of Scientific and Technical Information of the People's Republic of China and to determine its optimization directions. A content analysis of 28 provincial institutes of scientific and technical information’s official sites was carried out; the most powerful of them were identified in terms of resource and service potential, the level of organization of corporate cooperation based on consolidated digital platforms of multifunctional user service. It is proved that the level of efficiency of digital services of regional scientific and technical information systems directly depends on the level of the province’s economic development and the ability of its government to finance and technologically equip information industry centers activities, and to establish sustainable interaction of all subjects of the information market. Summarizing the results of the content analysis made it possible to identify reserves for improving the service capabilities of the Chinese information industry’s regional clusters, to design vectors for diversifying consulting, expert-analytical, cognitive services of provincial institutes of scientific and technical information, the development of integrated innovation-oriented intelligent service platforms operating based on artificial intelligence technologies.