Measurement and analysis of collaboration ability. The collaborative rate, collaborative breadth and collaborative depth
| DOI | https://doi.org/10.1108/EL-10-2016-0229 |
| Date | 03 April 2018 |
| Published date | 03 April 2018 |
| Pages | 270-285 |
| Author | Rongying Zhao,Xuqiu Wei |
| Subject Matter | Information & knowledge management,Information & communications technology,Internet |
Measurement and analysis of
collaboration ability
The collaborative rate, collaborative breadth
and collaborative depth
Rongying Zhao and Xuqiu Wei
School of Information Management, Wuhan University, Wuhan, China
Abstract
Purpose –Collaboration is an important way for scientific research. It attracts a large number of
researchers, and forms a series of measurement evaluation indicators. The purpose of this study further
enriches the evaluation systemof collaboration and provides new indicators to measure collaborationability
at author levelin order to identify the most appropriate potentialpartners.
Design/methodology/approach –The papers published during the period 2006-2015 and collected
from Web of ScienceCore Collection in library and information science(LIS) are regarded as data source. And
it defines and measuresthe collaborative rate, collaborative breadthand collaborative depth at author level.
Findings –The authors’research shows that collaboration is an important way in the scientific research
activities in LIS. Unfortunately, most author’s collaborative breadth and the collaborative depth are lower
than mean. Therefore, the author’s scope and stability of collaboration is further strengthened in future.
Authors can identify the mostappropriate potential partners according to author’s researchpurpose and the
region of the collaborativebreadth –the collaborative depth.
Originality/value –It further enrichesthe evaluation system of collaboration and provides new indicators
to evaluate collaborationability at author level. Authors can identify the most appropriatepotential partners
accordingto author’s collaboration ability.
Keywords Collaboration ability, Collaborative breadth, Collaborative depth, Collaborative rates
Paper type Research paper
1. Introduction
Social collaboration refers to interactionstaking place within a social context among at least
two scientists, institutionsor countries that facilitate the sharing of meaning and completion
of tasks with respect to a mutually shared,super-ordinated goal (Koseoglu, 2016). It has the
potential to solve complex scientific problems and promote various political, economic and
social agendas, such as democracy, sustainable development and cultural understanding
and integration (Sonnenwald, 2007). Therefore, collaborations are an essential part of
academic life, and the lone scholar in the ivory tower is a rare phenomenon nowadays
(Henriksen, 2016).The issue of collaboration has attracted more and more researchers.
Research has progressed through three ages: the individual, the institutional and the
national (Adams, 2013). Collaboration at the individual level (author level) mainly studies
collaboration among authors (Liu et al., 2015;McCarty et al., 2013;Yu et al., 2014).
Collaboration at the institutional level mainly studies collaboration among institutions
(Kasper et al., 2014;Ye et al., 2012). Collaboration at the national level mainly studies
collaboration among nations (Finardi and Buratti, 2016;Maisonobe et al., 2016).
This work is supported by National Social Science Foundation in China (Grant No.16BTQ055).
EL
36,2
270
Received25 October 2016
Revised30 May 2017
Accepted6 July 2017
TheElectronic Library
Vol.36 No. 2, 2018
pp. 270-285
© Emerald Publishing Limited
0264-0473
DOI 10.1108/EL-10-2016-0229
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0264-0473.htm
Collaboration among institutions or nations/regions is mainlybased on institutions/nations/
regions to which a researcher belongs. Therefore, to a certain extent, collaboration among
institutions or nations/regions can be said to be rooted in the collaboration among
researchers (authors).
How to measure collaboration ability and identify the most appropriate potential
research partners is the key to carry out collaborative research. To further enrich the
evaluation system of collaboration, this paper measures and analyses the collaboration
ability from three aspects (collaborativerate, collaborative breadth and collaborative depth)
at the author level. In the process, an author’s number of articles and number of
collaborative articles are comprehensively considered. The indicators of collaborative rate,
collaborative breadth and collaborative depth are also defined. And finally, the articles
published duringthe period 2006-2015 and collected from the Web of ScienceCore Collection
in information science and library scienceare regarded as the data source. First, it explores
the collaborative situation in library and information science (LIS) via statistics of the
number of articles, number of collaborativearticles and collaborative rate at the article level.
Second, it measures collaborative rate, collaborative breadth and collaborative depth and
analyses the main impact factors. Finally, the indicators of the collaborative breadth and
collaborative depth are comprehensively considered, and the characteristicsof collaboration
in LIS are discovered through dividing the region to identifythe most appropriate potential
research partners.
2. Background
With the deepening of scientific research collaboration, it gradually forms a series of
evaluation indicators, which are used to evaluate the collaboration ability in one discipline
or subject area. According to the difference of indicators, the studies are divided into two
types: single-indicatorstudy and multi-indicator study.
2.1 Single-indicator study
Single-indicator study refers to the statistical study of single indicator data. For example,
Newman (2001) studied a variety of statistical properties of networks, including the
numbers of papers written by authors, numbers of authors per paper, numbers of
collaborators that scientists have, existence and size of a giant component of connected
scientists and the degree of clustering in networks. Zhai et al. (2014) studied the evolution
and trend of collaboration networks in the field of informationsystems, and they found that
the average collaboration degree and co-authorship ratio of articles over time were on the
rise overall.
2.2 Multi-indicator study
Multi-indicator study is a comprehensive study of multiple indicator data. Schubert (2012)
proposed a partnership ability index. It combined the number of co-authors and the times
each of them acted as co-authors with a given author exactly the same way as Hirsch’s
h-index combines the number of publications and their citation rate. Wang et al. (2014)
introduced Schubert’s partnership ability index into China and analysed its own unique
theoretical and practical application value. Sabaghinejad et al.(2016)estimated the
partnership ability of Scientometricsjournal authors based on the Web of Science from 2001
to 2013 via this index.
Single-indicator study seems relatively simple. Although multi-indicator study
(partnership ability index) combined with a variety of indicator data seems relatively
complex, it ignores the maximum scope of collaboration and the maximum collaboration
Measurement
and analysis
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