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Scientific Collaboration in a Multidisciplinary Organization Revealed by Network Science

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Abstract

Multidisciplinary scientific organizations have sought to face the challenges of digital transformation through new governance models that optimize network collaboration and innovation. We studied the collaboration network from the long-term coauthoring system of a Brazilian multidisciplinary organization (Embrapa). The study shows that nodes degree distribution of the network is scale free and degree correlation analysis suggests a disassortative regime from competition and minimal but sufficient control that emerges as a hub-and-spoke pattern. The jobs of controller and researcher are twice as many occupied by males, except for the jobs of analyst, who act like network gatekeeper. With the largest number of individuals in product units, the southern region of the country is more likely to form clusters. Alternatively, hubs in thematic and ecoregional units in the Midwest have greater gravitational attraction, positioning themselves in the inner core of the giant component. The optimization of innovation by the organization should combine greater individual autonomy through improved human capital, with a universal labeling of units as, for instance, centers of innovation.

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Acknowledgements

The authors thank to Embrapa for providing open data that supported this work. The anonymous dataset explored in this research can be available on request to the corresponding author.

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Contributions

Conceptualization: IB; Methodology: IB; Formal analysis and investigation: IB; Writing—original draft preparation: IB; Writing—review and editing: PMS, AHO.

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Correspondence to Ivan Bergier.

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Conflict of interest

The authors are members of the studied organization, whose motivation is to find new organizational models that improve the capacity for scientific innovation based on ethical and transparency principles to cope with a digital world with increasing spread of misinformation and denial.

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Bergier, I., Santos, P.M. & Oster, A.H. Scientific Collaboration in a Multidisciplinary Organization Revealed by Network Science. SN COMPUT. SCI. 2, 4 (2021). https://doi.org/10.1007/s42979-020-00393-8

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