Article

# Modified collaborative coefficient: A new measure for quantifying the degree of research collaboration. Scientometrics, 84(2), 365-371

(Impact Factor: 2.18). 08/2010; 84(2):365-371. DOI: 10.1007/s11192-009-0100-4
Source: DBLP

ABSTRACT

Collaborative coefficient (CC) is a measure of collaboration in research, that reflects both the mean number of authors per
paper as well as the proportion of multi-authored papers. Although it lies between the values 0 and 1, and is 0 for a collection
of purely single-authored papers, it is not 1 for the case where all papers are maximally authored, i.e., every publication
in the collection has all authors in the collection as co-authors. We propose a simple modification of CC, which we call modified
collaboration coefficient (or MCC, for short), which improves its performance in this respect.

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• "One is the average number of authors per paper (COPP) at each stage. It's a widely used indicator of collaboration, which is in fact known as Collaboration Degree in previous literature (Savanur and Srikanth 2009). COPP is calculated stage by stage. "
##### Article: How are collaboration and productivity correlated at various career stages of scientists?
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ABSTRACT: Collaboration is believed to be influential on researchers’ productivity. However, the impact of collaboration relies on factors such as disciplines, collaboration patterns, and collaborators’ characters. In addition, at different career stages, such as the growth or the establishment career stages of scientists, collaboration is different in scale and scope, and its effect on productivity varies. In this paper, we study the relationships between collaboration and productivity in four disciplines, Organic Chemistry, Virology, Mathematics and Computer Science. Our study found that the productivity is correlated with collaboration in general, but the correlation could be positive or negative on the basis of which aspect of collaboration to measure, i.e., the scale or scope of the collaboration. The correlation becomes stronger as individual scientists progress through various stages of their career. Furthermore, experimental disciplines, such as Organic Chemistry and Virology, have shown stronger correlation coefficients than theoretical ones such as Mathematics and Computer Science.
Scientometrics 05/2014; 101(2):1553-1564. DOI:10.1007/s11192-014-1323-6 · 2.18 Impact Factor
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• "For this purpose, co-authorship analysis has been particularly recognised by some studies (e.g. Glanzel, 2001; Savanur and Srikanth, 2009) as being the most common tool in investigating the co-authorship relations and the quantitative patterns in scienti¯c collaboration. "
##### Article: Impact of Funding on Scientific Output and Collaboration: A Survey of Literature
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ABSTRACT: This document critically reviews the papers that investigated the impact of funding on scientific output and on scientific collaboration. For the output, the focus is on the number of articles as a measure of the scientific productivity and the number of citations that a paper received as an indicator of the quality. Various methodological approaches have been adopted (e.g. bibliometrics (a set of methods to analyse the scientific literature quantitatively), statistical analysis) for this purpose. Reviewing the literature revealed that although the general assumption of the positive effect of funding on scientific development is completely (or partially) acknowledged in some studies, one can also find some contradictory results. In addition, we note that analysing the impact of funding on scientific output has attracted more attention of the researchers while investigating the impact of funding on collaboration has been only recently taken into consideration. The paper concludes by comparing the major results and methodologies of the reviewed studies while highlighting the research gaps. Read More: http://www.worldscientific.com/doi/abs/10.1142/S0219649213500378
Journal of Information & Knowledge Management 12/2013; 12(04). DOI:10.1142/S0219649213500378
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• "There is growing interest in measuring research collaboration (Katz & Martin, 1997; Laudel, 2002). Although some studies have argued that the common measure of collaboration in academic research is co-authorship (Savanur & Srikanth, 2010), others have argued that not all collaborators appear as coauthors (e.g., collaboration can also be mentioned in acknowledgements). Furthermore, not all types of collaborative efforts are formally expressed in papers (e.g., advice on the research process) (Melin & Persson, 1996; Gordon, 1980). "
##### Article: Has globalization strengthened South Korea's National Research System? National and international dynamics of the triple helix of scientific co-authorship relationships in South Korea
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ABSTRACT: We trace the structural patterns of co-authorship between Korean researchers at three institutional types (university, government, and industry) and their international partners in terms of the mutual information generated in these relations. Data were collected from the Web of Science during the period 1968–2009. The traditional Triple-Helix indicator was modified to measure the evolving network of co-authorship relations. The results show that international co-authorship relations have varied considerably over time and with changes in government policies, but most relations have become stable since the early 2000s. In other words, the national publication system of Korea has gained some synergy from R&D internationalization during the 1990s, but the development seems to stagnate particularly at the national level: whereas both university and industrial collaborations are internationalized, the cross-connection within Korea has steadily eroded. KeywordsCo-authorship–International collaboration–University–industry–government relationship–South Korea–Triple Helix–R&D internationalization–Globalization–National research system–Innovation
Scientometrics 01/2012; 90(1):163-176. DOI:10.1007/s11192-011-0512-9 · 2.18 Impact Factor

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