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• W2498813204 abstract "Abstract In spite of vast studies performed on Science and Technology Collaborative Networks (STCNs) in recent decades, factors affecting the stability of these networks have rarely been investigated. In this study, 6 collaborative networks established between 1995 and 2005 in Iran, in the fields of nanotechnology, biotechnology, molecular medicine and herbal medicine, were evaluated. Conducting a qualitative research, and using multiple-case study method, we collected related data adequately from in-depth interviews with key informants, survey, and archived documents, and identified the stability factors of STCNs. In this paper, a tentative conceptual model is proposed for classification of stability factors in formal STCNs. Employing this model, 27 identified and screened stability factors were classified into 2 main categories; including internal factors (network management, network formation processes, collaboration mechanisms in the network and characteristics of network members) and external factors (collaboration infrastructures and network environment). Designed model was evaluated by conducting an extensive survey which provides feedbacks from the representatives of network members and other informed people on the primary model. In total, 112 individuals from 83 affiliated organizations of 6 selected networks participated in this survey. Confirmatory factor analysis (CFA) method was used to evaluate the goodness of fit of the proposed model which indicated that each structural component of the model has suitable fit, separately. In addition, the whole model offers a good fitting and it can be reliably used to achieve the research goal only by omitting two of considered factors." @default.
• W2498813204 created "2016-08-23" @default.
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• W2498813204 date "2017-09-01" @default.
• W2498813204 modified "2023-09-27" @default.
• W2498813204 title "A model for investigating the stability factors in formal science and technology collaborative networks: A case study of Iran" @default.
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• W2498813204 doi "https://doi.org/10.1016/j.techfore.2016.07.039" @default.
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