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Scientific collaboration is becoming a common pattern in the social organization of knowledge production. The paper tries to figure out the relationship between scientific collaboration team size and scientific output.

Based on ESI database from year 2009–2019, the paper describes changes of collaboration team size from one author to more than 10 authors in 22 disciplines. Kernel density estimation and multidimensional kernel density estimation method are used to calculate optimal collaboration team size and appropriate collaboration team size in 22 disciplines. As bandwidth is one of the major issues in construction of kernel density estimation, the paper uses five different algorithms to calculate bandwidth. The method with the lowest mean absolute percentage error is chosen. Robustness test is conducted based on different sets of data.

The results show that scientific collaboration becomes more widely and deeply. As time goes by, collaboration team size is becoming larger and larger. Natural science disciplines have larger collaboration team size and faster growth rate than social science disciplines. Considering both qualitative and quantitative measures, the paper proves the universality of optimal and appropriate scientific collaboration team size among 22 disciplines and calculates the specific number.

The paper tries to investigate the law of scientific collaboration team size variation and provide a full picture of evolution of collaboration team size among 22 disciplines in 10 years. The paper first applies distribution method to figure out the relationship between scientific collaboration team size and scientific output and provides optimal collaboration team size and appropriate collaboration team size.

Various forms of regional cooperation in East Asia have greatly increased in the past two decades. Scientific collaboration is beneficial for both scientifically lagging countries (SLCs) and scientifically advanced countries (SACs) with respect to their S&T capacity and thus economic prosperity. This paper aims to provide a comprehensive description of intra‐regional scientific collaboration in East Asia from 1985 to 2008 with the 10+3 (ASEAN ten plus China, Japan and South Korea) framework.

The paper uses co‐authored articles embodied by Science Citation Index Expanded (SCI‐Expanded) to indicate cross‐border scientific collaboration.

Data show that heterogeneity in the publication output across East Asian countries is decreasing. Intra‐ASEAN, intra‐ Northeast Asia, as well as ASEAN and Northeast Asia scientific collaboration greatly improved since 1997.

This paper discusses factors influencing international scientific collaboration and focuses on explaining the impact of regional integration. Finally, it offers further suggestions on East Asian integration from the perspective of scientific collaboration.

The purpose of this paper is to explore the hypothesis that collaboration was a key characteristic of Cuban science to maintain their scientific capacity during a period of economic restrictions and an important feature of Cuban science policy and practice for the benefit of society.

Collaboration was studied through Cuban scientific publications listed in PubMed for the period 1990-2010. The search was carried out using the advanced search engine of PubMed indicating < Cuba > in the affiliation field. To identify participating institutions a second search was performed to find the affiliations of all authors per article through the link to the electronic journal. A data set was created to identify institutional publication patterns for the surveyed period. Institutions were classified in three categories according to their scientific production as Central, Middle or Distal: the pattern of collaboration between these categories was analysed.

Results indicate that collaboration between scientifically advanced institutions (Central) and a wide range of national institutions is a consequence of the social character of science in Cuba in which cooperation prevails. Although this finding comes from a limited field of biomedical science it is likely to reflect Cuban science policy in general.

Using bibliometric tools the study suggests that Cuban science policy and practice ensure the application of science for social needs by harnessing human resources through national and international collaboration, building in this way stronger scientific capacity.

In this article, the authors explore the emotional dimension of the strategies that researchers carry out to foster collaboration within research groups in science.

The authors have carried out fieldwork based on semi-structured interviews with members of high-performance research groups, supported by the analysis of ethnographic observations in the local work contexts of several of these groups.

As a result, the authors start from the representations of the principal investigators interviewed about collaboration, as a dynamic between the individuals involved and the group, to describe two forms of leadership strategies: ego-centered or group. Hence, the authors highlight that the emotional work of IPs consists of combining both strategies by activating and deactivating affection, warmth and spontaneity in interactions. The authors conclude by reviewing the contributions and some potential lines of study.

The main contributions and conclusions must be regarded considering several limitations of our work. First, the authors have focused on high-performance groups, so it would be expected that the research groups that do not have the support of European Research Council (ERC) do not present the observed dynamics. Concerning the analysis, the authors have focused on the link between situational (personal interaction) and organizational scales. Although the authors have attended social factors that imply the structure and changes of the professional sector of science (Whitley, 2000, 2014), future publications will allow the authors to delve into relationships on a broader scale, associating collaboration patterns and discursive positions. The authors will focus on (1) roles and social profiles and (2) features of scientific culture and its recent configuration.

The authors affirm that the emotional field is key to understanding how groups and individuals respond to these profound changes. In their work, scientific professionals do not only act based on rational and instrumental criteria but also driven by habits, affective networks and inertia of their organizational cultures. In this paper, the authors provide theoretical and practical keys to understand the complexity that collaboration creates within research groups as a contradictory reality that consists of a constant movement of individuals and the group.

As many of the interviewees expressed, there are no adequate spaces to learn and reflect on leadership and collaboration in science. The authors are science workers who are responsible for imagining and deciding how the authors want their research groups to function. Institutions must ensure the means so that this task can be carried out. Hopefully, this article will contribute to this irrevocable project.

The authors’ aim is to understand how well-known groups operate in their field, with a high level of resources and productivity, in order to identify and promote cutting-edge strategies in different scientific branches. Moreover, the authors want to recognize the importance of institutional infrastructures. For this reason, giving them a place in the framework of management studies allows to submit this issue to public debate for a wide audience of social scientists. Moreover, this permits to inquire about cross-disciplinary subjects, such as social and organizational psychology, sociology of work, studies about science and management studies.

Synergy indicators and social network analysis (SNA), as practical tools, provide the possibility of explaining the pattern of scientific collaboration and visualization of network relations. Recognition of scientific capacities is the basis of synergy. The present study aims to measure and discover the synergistic networks of COVID-19’s top papers at the level of co-authorship, countries, journals, bibliographic couples and titles.

The synergy indicator, co-authorship co-citation network analysis methods were applied. The research population comprises COVID-19’s top papers indexed in Essential Science Indicator and Web of Science Core Collection 2020 and 2021. Excel 2016, UCINET 6.528.0.0 2017, NetDraw, Ravar Matrix, VOSviewer version 1.6.14 and Python 3.9.5 were applied to analyze the data and visualize the networks.

The findings indicate that considering the three possible possibilities for authors, countries and journals, more redundancy and information are created and potential for further cooperation is observed. The synergy of scientific collaboration has revealed that “Wang, Y,” “USA” and “Science of the Total Environment” have the most effective capabilities and results. “Guan (2020b)” and “Zhou (2020)” are bibliographic couplings that have received the most citations. The keywords “CORONAVIRUS DISEASE 2019 (COVID-19)” were the most frequent in article titles.

In a circumstance that the world is suffering from a COVID-19 pandemic and all scientists are conducting various researches to discover vaccines, medicines and new treatment methods, scientometric studies, and analysis of social networks of COVID-19 publications to be able to specify the synergy rate and the scientific collaboration networks, are not only innovative and original but also of great importance and priority; SNA tools along with the synergy indicator is capable of visualizing the complicated and multifaceted pattern of scientific collaboration in COVID-19. As a result, analyses can help identify existing capacities and define a new space for using COVID-19 researchers’ capabilities.

The environment in high-tech industries is highly dynamic, and after COVID-19, it has become even more unpredictable. Hence, it has become critical for firms to develop strategies to cope with a highly dynamic environment. This paper aims to analyze how the impact of the scientific collaboration networks with URIs (universities and research institutes) on firm innovation performance is contingent on technological and market dynamics.

Using a sample of 174 Chinese firms in the new-energy vehicle industry during 2004–2015, the authors applied a random-effects negative binomial modeling approach to model these relationships.

A broad and strong scientific collaboration network promotes firm innovation network effects are contingent on technological and market dynamics. While technological dynamics strengthen the effect market dynamics weaken it due to the different purposes of collaboration for firms and URIs.

Firms should adjust the structure of scientific collaboration networks with URIs when facing different environments. The government should encourage firms to jointly research with diverse URIs and play an active role in stabilizing market environments.

This study contributes to the academic debate on university-industry scientific collaborations. Applying the temporary competitive advantage (TCA) framework, we provide nuances to the literature that studies the factors that condition the effects of networks. This study also adds to the research on firm scientific collaboration networks by measuring networks based on the coauthorship between firms and URIs.

Although the role of enterprise in R&D is broadly acknowledged, few attempts have been made to gather data for analyzing the nature and scope of private sector collaboration. This study aims to deliver empirical results based on quantitative data to gain insight into the role of private enterprise as an indispensable actor in scientific development and innovation.

The study aimed to deliver empirical results based on quantitative data to gain insight into the role of private enterprise as an indispensable actor in scientific development and innovation. To this end, an analysis was conducted of the contribution made by Spanish business, focusing on the 50 most active companies in terms of internationally visible scientific output, from three perspectives.

The findings provide insight into business involvement in the R&D system based on: research papers published; national, international and sectoral collaboration patterns; structural patterns; and the identification of the most prominent companies from a systematic comparison of their research results and their position in the resulting collaboration network.

Bibliometric analyses do not measure all types of publications. Indicators are usually based on data in the Thomson Reuters databases, which are regarded as being representative of peer‐reviewed, publicly accessible papers with high international visibility and impact. The Thomson Reuters databases feature a series of advantages that make them indispensable for studies on scientific collaboration.

One of the core ideas of this study is the emphasis on the essential role of collaboration in improving scientific results, as borne out by the correlation between the clustering coefficient and the hybrid indicators. The findings also provide proof of the success of strategies for institutional collaboration. The foregoing shows that the application of hybrid indicators to institutional aggregates yields novel results not explored in preceding studies.

The purpose of this paper is to analyze the scientific collaboration of institutions and its impact on institutional research performance in terms of productivity and quality. The researchers examined the local and international collaborations that have a great impact on institutional performance.

Collaboration dependence measure was used to investigate the impact of an institution on external information. Based on this information, the authors used “index of gain in impact through collaboration” to find the impact of collaborated publications in institutional research performance. Bibliographic data between 1996 and 2010 retrieved from Scopus were used to conduct current study. The authors carried out the case study of top institutes of Pakistan in terms of publication count to elaborate the difference between high performing institutions and those who gain disproportionally in terms of perceived quality of their output because of local or international collaboration.

The results showed that the collaboration of developing countries institutes on international level had a great impact on institutional performance and they gain more benefit than local collaboration. Altogether, the scientific collaboration has a positive impact on institutional performance as measured by the cumulative source normalized impact per paper of their publications. The findings could also help researchers to find out appropriate collaboration partners.

This study has revealed some salient characteristics of collaboration in academic research. It becomes apparent that collaboration intensity is not uniform, but in general, the average quality of scientific production is the variable that most often correlates positively with the collaboration intensity of universities.

The purpose of this paper is to provide insights on the improvement of academic impact and social attention of Chinese collaboration articles from the perspective of altmetrics.

The authors retrieved articles which are from the Chinese Academy of Sciences (CAS) and indexed by Nature Index as sampled articles. With the methods of distribution analysis, comparative analysis and correlation analysis, authors compare the coverage differences of altmetric sources for CAS Chinese articles and CAS international articles, and analyze the correlation between the collaborative information and the altmetric indicators.

Results show that the coverage of altmetric sources for CAS international articles is greater than that for CAS Chinese articles. Mendeley and Twitter cover a higher percentage of collaborative articles than other sources studied. Collaborative information, such as number of collaborating countries, number of collaborating institutions, and number of collaborating authors, show moderate or low correlation with altmetric indicator counts. Mendeley readership has a moderate correlation with altmetric indicators like tweets, news outlets and blog posts.

International scientific collaboration at different levels improves attention, academic impact and social impact of articles. International collaboration and altmetrics indicators supplement each other. The results of this study can help us better understand the relationship between altmetrics indicators of articles and collaborative information of articles. It is of great significance to evaluate the influence of Chinese articles, as well as help to improve the academic impact and social attention of Chinese collaboration articles.

To the best of authors’ knowledge, few studies focus on the use of altmetrics to assess publications produced through Chinese academic collaboration. This study is one of a few attempts that include the number of collaborating countries, number of collaborating institutions, and number of collaborating authors of scientific collaboration into the discussion of altmetric indicators and figured out the relationship among them.

How does university-firm collaboration affect the performance of both universities and firms? The purpose of this paper is to evaluate university-firm collaborations aimed at expanding the treatment effects of collaboration ambition on university academic performance as well as collaboration ambition focused on the firm’s production of innovation and financial performance for the top 110 US universities and the top 200 US R&D performing firms.

“Two studies, based on the three archival data sets (National Bureau of Economic Research-Rensselaer Scientific Papers Database and the Harvard Dataverse Network (DVN) US Patent Citations database and Compustat database), are undertaken in the top 110 US universities and the top 200 US R&D performing firms.” The study introduces a theoretical model that explicitly addresses collaboration diversity, number of collaborations, knowledge stock and the endogeneity problem that is generated by self-selection of collaboration ambition in university and firm’s performance.

The results suggest that the effects of adopting proactive collaboration decision on academic performance are insignificant in the firm subsample. However, more interestingly, the authors find supporting evidence of the negative impact of collaboration on university groups. The authors also find that collaboration diversity, knowledge stock and collaboration ambition lead to stronger firm performance but the number of collaborations is smaller on firm performance. Furthermore, the authors find that collaboration ambition moderates the positive effect of the number of collaborations on firm performance.

University-firm collaboration is a multifaceted relationship, suggesting that the empirical analysis can be interpreted through the university and the firm view to enhance the understanding of the collaboration for performance creation. This study articulates the positive role of collaboration diversity, knowledge stock and collaboration ambition and the negative role of the number of collaborations on university-firm collaboration in terms of university and firm performance. Moreover, proactive collaboration ambition has the positive effect of a higher number of collaborations on firm performance. The authors conclude that policy should refrain from overly focusing on collaboration diversity, number of collaborations, knowledge stock and collaboration ambition, and the authors consider the interactions between the number of collaborations and collaboration ambition on university-firm collaboration when discussing their effects on mutual performance.

This study demonstrates the effects of university-firm collaboration on academic performance. In addition, the authors discuss the factors that influence collaboration to help the firm to increase its innovation and financial performance. Therefore, it would be interesting to see simultaneously how university-firm collaboration affects the performance of both partners.