| Research on the influencing factors framework of data demand management of university scientific researchers北大核心CSSCI |
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| 基金项目： | Research on National Digital Academic Resources Information Security System, (14ZDB168)；National Office for Philosophy and Social Sciences, NPOPSS |
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| 摘 要： | The environment and pattern of scientific research are developing towards digital, open and community-oriented , and influenced by the increasingly diversified data resources and the mature of various methods. All these make the researchers' demand becoming more complicated and deepened. The evolution of scientific research puts forward higher requirement for the data demand management of collegial researchers. We constructed an analytical framework of the influencing factors of data demand management for scientific researchers based on the grounded theory. The interaction of key elements involved in the framework was analyzed , aiming to reveal the influence mechanism of key factors on researchers, data demand management. This research is composed of four parts research problem generation data collection data processing and theory construction. Staged collection method was used in data collection mainly through personal indepth interview and focus group meeting and the data we collected was supplemented and verified by the data and comments in various scientific research platforms. Data standardization and reduction was carried out by the qualitative analysis software Nvivo 12.0 , and the original data was coded in three-level: Open coding , spindle coding and selective coding. The USCT framework we constructed contains 8 main categories: Personal ability characteristic , user perception , personalized service, knowledge service, task context , mobile information context , technology application and technology fit , involving 24 categories and 67 initial concepts. All categories and concepts were generalized into 4 layers: Key layer (user dimension), guarantee layer (service dimension), driven layer (context dimension) and foundation layer (technology dimension). In the subsequent analysis of interactive relationship and internal correlative mechanism between main categories and data demand management we found personal ability characteristic of user personalized service and task context to be the most direct impact factor on data demand management while user perception knowledge service mobile information context technology application and technology fit work in an indirect way. The USCT model framework has several positive effects: 1) it contributes to the construction and perfection of the conceptual system and framework of scientific research data demand management 2 it provides a reliable guiding analysis model for the construction of a science data service platform to promote scientific research and innovation. We innovatively constructed an analysis framework for the influencing factors of data demand management of university researchers. This framework organically integrates " user” (scientific researcher, subject librarian), “services", “context” and “technology” into one system. We attempt to guide and develop the researcher's scientific data needs under their knowledge environment through computer information technology and ultimately guarantee the provision of suitable service. Further demonstration and service practices are needed to verify and perfect the theory. Follow-up studies can take “user-context-service-technology” as the main line for empirical research and explore the external features and internal path mechanisms of data demand management in all domains. 6 figs. 3 tabs. 49 refs. © 2019, Editorial Office of Journal of Library Science in China. All rights reserved.
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