Large Teams Develop and Small Teams Disrupt Science and Technology

Authors: Lingfei Wu, Dashun Wang, James A. Evans


It is seen that larger organisations working for science and technology easily solve challenges accompanying the modern world that demand integrative solutions. Employees working in big organizations think and act oppositely from those working in smaller companies. Larger teams produce less innovative ideas, negate the views of their teammates and only work on safe bets. However, smaller organizations take risks more frequently and work on more innovative concepts as they have more to acquire than to sacrifice. This information escorted us to further inspect the outcomes of small and large organizations for the progression of science and technology. Also, to determine the various methods used by these teams to gather background data.
It was seen that research articles from larger patent companies were cited more often. Even so, the number of citations cannot bring about such contributions. For instance, two eminent articles one related to the BTW model and the second about Bose-Einstein condensation had received equal citation count. The citations related to the former article only mentioned the BTW model without the reference to the research paper. However, Bose-Einstein condensation was always co-cited along with the article. The difference was that the BTW model pitched in innovative research whilst the Bose-Einstein condensation reviewed and enhanced the potential of previous research experiments. So it was basically decided upon whether the new ideas sabotaged or cultivated the available scientific research.


Datasets of research articles, patents and software published and developed between 1900-2014 were made from Web of Science (WOS). Dataset of scholars with similar names was made separately and articles that were self-cited were removed from the dataset. Nobel Prize-winning articles were also grouped. A group of government financial funded research articles were created. Another dataset included articles from different subjects of research and journals.
Linear regression was applied to the collected data to determine the quality and quantity of disruption.

Results and Discussion

A survey was conducted to determine if the above-mentioned point was valid. It was measured by assigning −1 to disruptive articles and +1 to developing articles. Nevertheless, the BTW model was declared disruptive among the top 1% and Boss-Einstein was in the bottom 3%. 2% of the disruptive articles were Nobel Award victors. Review articles were cultivated but the original work cited in them was disruptive. Articles with titles having words like ‘introduce’, ‘advance’ or ‘change’ were declared more troublesome compared to those giving the vibes of development such as ‘confirm’, ‘demonstrate’ or ‘model’. The graph below shows quantification of disruption.

Observations of the past 60 years reveal that patents and articles from big teams became less disruptive as the team members increased. Research articles published by a single author were found 72% more disrupting in contrast with those written by five or more authors.
The magnitude of disruption increases when research work exhibits a strong significant impact. Articles with considerable impact issued by small teams were highly disrupting when compared with high impact research papers published by bigger teams. No significant disruption was observed based on subjects and time frame. It was assumed that small teams produce more theoretical innovations and are more disruptive whereas large teams report experimental works but that was not the case. Graph a shows the effect of team size and impact percentile on disruption and b shows disruption among subjects.

Smaller teams focus on old research concepts which are less notable but larger teams aim directly on recent and modern research ideas and receive more citation count. However, efficacious research published by small teams generates a ripple effect subsequently resulting in the victory of bigger teams. This study suggests that small teams target challenging research objectives with the risk of profit or loss. Larger teams are considered sensitive to losing so they usually aim at refining the recent research works. Articles published during 2004-2014 showed that small teams which received financial aid from the government produced more developmental research. Small organizations bring about revolutionary innovations for the improvement of science and technology. Government and funding agencies should consider the importance of smaller research groups which tend to escalate the cutting edge of data despite the point that larger teams cultivate this data.

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