کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5036893 1472384 2017 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Scientific collaboration in indigenous knowledge in context: Insights from publication and co-publication network analysis
ترجمه فارسی عنوان
همکاری علمی در دانش بومی در زمینه: بینش از تجزیه و تحلیل شبکه انتشار و همکاری انتشار
موضوعات مرتبط
علوم انسانی و اجتماعی مدیریت، کسب و کار و حسابداری کسب و کار و مدیریت بین المللی
چکیده انگلیسی


- An analysis of research capability in the field of traditional medicine is presented.
- A dynamic adaptation of Revealed Technological Advantage for papers is proposed.
- Co-authorship networks in traditional medicine for selected cases is explored.

Scientific collaboration has been cited as a major stimulant in innovation and a major component for the development of indigenous technologies particularly in countries invested in rapid technological catch-up in East Asia and Southeast Asia. In this study, we assess the comparative advantage of the selected economies and employ a network perspective to drill down to the case study of indigenous knowledge, using the traditional medicine sector - a focus indigenous industry of several Asian economies - to understand how the State, Industry and Universities link to drive innovation in this growing field. From our selected economies in East Asia, we identified three network models that describe the outcomes of the innovation strategies in place, a network-based extension of previous studies. We examine publication output and co-publication network structures to investigate the comparative advantage and composition of the research networks in the various economies. Our results suggest that the university-centric model remains the most popular, with Hong Kong appearing to attain the most functional innovation system with a competitive selection environment and high comparative advantage in this field. We propose this methodology as a means to explore the scientific infrastructure of a specific sector, thereby acting as a precursor to forecasting potential technological spill-over and growth in specific sectors.

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ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Technological Forecasting and Social Change - Volume 117, April 2017, Pages 57-69
نویسندگان
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