Team Size, Research Variety, and Research Performance: Do Coauthors’ Coauthors Matter?

Zhu, Nibing; Liu, Chang; Yang, Zhilin

doi:10.1016/j.joi.2021.101205

Cited by 20 publications

(8 citation statements)

References 59 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In fact, the benefits of team size were shown not to follow a linear growth pattern. With the continued "inflation" of collaboration size, citation rates appeared the tendency of reduction, which presented an inverted U-shaped relationship 7,57,58 . As Wu et al 13 found, large teams tend to develop existing science and technology more than small teams, resulting in fewer disruptive innovation breakthroughs.…”

Section: Discussionmentioning

confidence: 99%

“…As Wu et al 13 found, large teams tend to develop existing science and technology more than small teams, resulting in fewer disruptive innovation breakthroughs. Increased team size is often accompanied by greater diversity among team members 58 , introducing more collective intelligence and innovative perspectives. There are exceptions, such as very diverse small groups and large, highly homogenous teams.…”

Section: Discussionmentioning

confidence: 99%

“…Despite controlling for the variable of team size, the present study still found an inverted U-shaped distribution in the relationship between collaboration diversity and societal impact, indicating the relatively greater importance of diversity in collective decision-making performance compared to team size. Zhu et al 58 discovered that research team members' own research diversity played a moderating role in the relationship between team size and the influence of the research. In any case, our conclusions need to be interpreted with caution, as the relationship between size and diversity may be reversed under other conditions.…”

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

The inverted U-shaped relationship between knowledge diversity of researchers and societal impact

Wang

Gan²,

Yang³

2022

Sci Rep

View full text Add to dashboard Cite

With the increasing importance of interdisciplinary research, some studies have focused on the role of reference diversity by analysing reference lists of published papers. However, the relationship between the knowledge diversity of collaborating team members and research performance has been overlooked. In this study, we measured knowledge diversity through the disciplinary attributes of collaborating authors and research performance (understood as societal impact) through altmetric data. The major findings are: (1) The relationship between interdisciplinary collaboration diversity and societal impact is not a simple linear one, showing an inverted U-shaped pattern; and (2) As the number of collaborative disciplines increases, the marginal effects diminish or even become outweighed by the costs, showing a predominance of negative influences. Hence, diversity in interdisciplinary collaboration does not always have a positive impact. Research collaborations need to take into account the cost issues associated with the diversity of member disciplines.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

The inverted U-shaped relationship between knowledge diversity of researchers and societal impact

Wang

Gan²,

Yang³

2022

Sci Rep

View full text Add to dashboard Cite

show abstract

“…It is noted that productivity is stable when scientific collaboration reaches a certain position (Chen and Sun, 2010). Zhu found that research team size and scientific output impact exhibit an inverted-U shaped relationship (Zhu et al, 2021). Based on four research fields, Guimer a suggested that "universal" set of optimal value of team size might exist (Guimer a et al, 2005).…”

Section: Scientific Collaboration Team Sizementioning

confidence: 99%

The exploration in the size of scientific collaboration team using kernel density estimation

Shan

2022

AJIM

View full text Add to dashboard Cite

PurposeScientific 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.Design/methodology/approachBased 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.FindingsThe 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.Originality/valueThe 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.

show abstract

“…Scientific collaboration is a prerequisite for enhancing the efficiency and productivity of scientific research [ 24 ]. For example, team building through scientific analysis collaboration enables scholars with complementary skills to cooperate with each other for conducting scientific research [ 25 ]. Kretschmer researched the cooperative relationship network and proposed the concept of the co-authorship network [ 26 ].…”

Section: Introductionmentioning

confidence: 99%

Contact Tracing Research: A Literature Review Based on Scientific Collaboration Network

Zhu

Niu³

2022

IJERPH

View full text Add to dashboard Cite

Contact tracing is a monitoring process including contact identification, listing, and follow-up, which is a key to slowing down pandemics of infectious diseases, such as COVID-19. In this study, we use the scientific collaboration network technique to explore the evolving history and scientific collaboration patterns of contact tracing. It is observed that the number of articles on the subject remained at a low level before 2020, probably because the practical significance of the contact tracing model was not widely accepted by the academic community. The COVID-19 pandemic has brought an unprecedented research boom to contact tracing, as evidenced by the explosion of the literature after 2020. Tuberculosis, HIV, and other sexually transmitted diseases were common types of diseases studied in contact tracing before 2020. In contrast, research on contact tracing regarding COVID-19 occupies a significantly large proportion after 2000. It is also found from the collaboration networks that academic teams in the field tend to conduct independent research, rather than cross-team collaboration, which is not conducive to knowledge dissemination and information flow.

show abstract

Team Size, Research Variety, and Research Performance: Do Coauthors’ Coauthors Matter?

Cited by 20 publications

References 59 publications

The inverted U-shaped relationship between knowledge diversity of researchers and societal impact

The inverted U-shaped relationship between knowledge diversity of researchers and societal impact

The exploration in the size of scientific collaboration team using kernel density estimation

Contact Tracing Research: A Literature Review Based on Scientific Collaboration Network

Contact Info

Product

Resources

About